1. 1
Smart Building
May 10th
2016
Faculty Advisor: Erin Bell
Industry Advisor: Kevin O’Maley and Eric Kruger– City of Manchester DPW
Project Group: Michael Langelier (ME), Jasmine Seguin (ME), Ryan Vickers
(CiE), and Brad Casperson (CiE)

2. 2
Disclaimer
This document is provided as part of the requirements of Civil Engineering course CIE 784,
Project Planning and Design, at the University of New Hampshire. It does not constitute a
professional engineering design nor a professional land-surveying document. Although the
information is intended to be accurate, students, instructors, and the University of New
Hampshire make no claims, promises, or guarantees about the accuracy, completeness, or
adequacy of the information. The user of this document shall ensure that its use does not violate
New Hampshire law with regard to professional licensing and certification requirements,
including any work resulting from this student-prepared document required to be under the
responsible charge of a licensed engineer or surveyor.

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Table of Contents
Introduction .......................................................................................................................................6
Scope of Work ...................................................................................................................................8
Bill of Materials ...............................................................................................................................10
Proposed Schedule............................................................................................................................11
Strain Gages.....................................................................................................................................13
How to Apply the Strain Gage .......................................................................................................14
Signal Conditioning: Amplification and Range Matching ................................................................15
SAP2000 Modeling ..........................................................................................................................18
Joist Dimensions...........................................................................................................................18
Loading........................................................................................................................................22
Deadweight Load ......................................................................................................................22
Roofing Load............................................................................................................................22
Snow Load................................................................................................................................22
Model Analysis.............................................................................................................................25
Data Analysis ...................................................................................................................................28
Preliminary Testing at UNH..........................................................................................................28
On-Site Testing at Hillside Middle School......................................................................................29
Closing Comments ...........................................................................................................................31
Future Work.................................................................................................................................31
Recommendations for Future Groups .............................................................................................32

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List of Figures
Figure 1: Hillside Middle School Aerial Photo .............................................................................. 8
Figure 2: Full Bridge Strain Gage Circuit..................................................................................... 13
Figure 3: Strain Gage before the adhesive is applied ................................................................... 14
Figure 4: Signal Amplifier that will be used................................................................................. 16
Figure 5: Steel Member in Hillside Middle School where sensors will be applied...................... 17
Figure 6: Wind Rose for Manchester, NH .................................................................................... 18
Figure 7: Location of Interest due to High Snow Loading Conditions......................................... 19
Figure 8: Selected Joist for SAP2000 Analysis ............................................................................ 19
Figure 9: Section Properties of Designed Bracing........................................................................ 20
Figure 10: Section Properties of Designed Top & Bottom Chords .............................................. 21
Figure 11: Rendered Views of Joist Created in SAP2000 ............................................................ 21
Figure 12: ASCE 7-10 Values for Ground Snow Loads............................................................... 23
Figure 13: Drifts Formed at Windward and Leeward Steps ......................................................... 23
Figure 14: Configuration of Snow Drifts on Lower Roofs........................................................... 24
Figure 15: ASCE 7-10 Snow Load Calculation............................................................................ 24
Figure 16: Predicted Stress Distribution due to Snow Loads ....................................................... 25
Figure 17: Predicted Deformation due to Snow Loads................................................................. 25
Figure 18: Graphical Representation of Strain Calculation in Comparison to 60% of Yielding
Strain............................................................................................................................................. 26
Figure 19: Location of Vulnerable Member ................................................................................. 27
Figure 20: Predicted Stress Distribution due to 320 lbs ............................................................... 27
Figure 21: Force v. Voltage plots of preliminary testing of strain gauge set up on flat bar; a)
Voltage read from the bridge module, b) Voltage read from signal conditioner, c) relationship
between voltage readings from the Bridge Module and the Signal Conditioner .......................... 28
Figure 22: Strain measurements from testing at Hillside Middle School vs. Strain values from
SAP2000 model ............................................................................................................................ 29

5. 5
List of Tables
Table 1: Products with Descriptions and Cost.............................................................................. 10
Table 2: Proposed Gant Chart......................................................Error! Bookmark not defined.1
Table 3: Fall Semester Project Schedule .....................................Error! Bookmark not defined.1
Table 4: Spring Semester Project Schedule .................................Error! Bookmark not defined.2
Table 5: Summary of Strain Calculations from SAP2000 ........................................................... 26
Table 6: Predicted Strain due to Incrimental 100 lb Loading ....................................................... 27
Table 7: RACI Chart..................................................................................................................... 32

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Introduction
Last winter the city of Manchester spent upwards of $100,000 on snow removal from
public facilities. The city’s Chief Facilities Manager, Kevin O’Maley, was concerned that the
city of Manchester was spending too much money on snow removal. Over the past few harsh
winters Kevin learned through experience that many of the buildings that were requesting for
snow removal were actually in no real danger of structural failure. When a school contacts the
DPW and addresses their concerns, Kevin has to often respond by hiring a structural engineer to
conduct an inspection before making the decision to spend money on the labor to remove the
snow. Alongside Kevin in these frequent inspections was Rich Roberts, a structural engineer in
Manchester. In many cases, Rich & Kevin came to the same conclusion; the building’s structural
integrity was not in danger. In some cases, an inspection is not enough to subdue fears of
structural failure, and Kevin would be pressured to remove snow from the roof.
The goal of this Senior Capstone Project was to develop a data acquisition & decision
making protocol that would prompt an alarm when there is structural danger in a designated
school. Most of Manchester’s public works facilities are integrated into the Building Automation
System (BAS). This system conducts data acquisition and is programmed with numerous
decision making protocol parameters. The BAS tracks numerous variables in Manchester’s
public buildings, such as temperature, lightning, and CO2 levels. All of this data is stored and
analyzed in real time to alert faculty or complete an automated sequence. The DPW can make
adjustments to turn lights on or even turn fans on when CO2 levels are too high. This system’s
alerts are constraints that are set for a specific sensor integrated into BAS. If these constraints are
surpassed, an alarm will be prompted.
This project aimed at picking a school in Manchester, finding the most potentially
vulnerable areas of the school, modeling the most vulnerable member in that area of the school
with large snow drifts, installing a system capable of measuring strain on the school’s vulnerable
structural member, and integrating the system into the DPW’s BAS. After installing strain gages
on the critical structural joist, a decision making protocol that would prompt an alarm in cases
where the structural integrity is in danger was developed. With research, modeling, and
experimentation; we aimed to begin research and implementation of a system that can accurately

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monitor snow loads. In the future, this system will monitor the building’s structural integrity and
will hopefully spread to additional public facilities.

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Scope of Work
To achieve an accurate and reliable monitoring system there are numerous variables to
take into consideration. Picking a building where the system was to be installed on was the first
thing to be decided. There are numerous schools that have removed snow during the winter
seasons despite the lack of risk. Hillside Middle School’s roof design made it a great candidate
for this project.
Figure 1: Hillside Middle School Aerial Photo
Notice the geometry of the building in Figure 1, the arrows show the areas that had the
most potential of developing large snow drifts in the winter. The roof of the first floor is highly
susceptible to large snow drifts, especially close to the sides of the second floor. Snow drifts are
dangerous because of the weight distributions they produce. Hillside Middle School’s structural
members are mainly steel. Steel is good for this project because its behavior is predictable in the
elastic region, up to the “yield point” stress. It is extremely important to note that for this entire
project that there was an assumption that Hooke’s Law is true. If the applied stress stays below
this point, the steel will return to its original shape when unloaded (the mechanical properties
will remain the same). Using the DPW’s original structural and architectural drawings of Hillside
Middle School, the selected joist could be modeled. The SAP2000 analysis data allowed us to
purchase strain gauges which measured the correct magnitude of strain predicted by the model.

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Experimental loading testing at UNH allowed us to confirm the linear elastic behavior through
our strain gauge system. Following this, the system was applied to the selected joist location that
was analyzed in the model. Lastly, field tests were conducted to verify our model’s accuracy.

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Bill of Materials
Table 1: Products with Descriptions and Cost
Product Model No. Procurement Type Price Qty Total Cost
Pre-Wired Strain Gages KFH-20-
120-C1-
11L1M2R
Off-shelf; Omega
website
$120 ea.
(for a pack
of 10)
2 $240
Bridge/Strain Gage Signal
Conditioner
DMD4059 Off shelf; Omega
website
$375 ea. 1 $375
Strain Gage Bridge
Completion Module
BCM-1 Off shelf; Omega
website
$85 1 $85
Rapid Adhesive Z70 Off shelf; Omega
website
$68 1 $68
Accelerator for Z70 BCY01 Off shelf; Omega
website
$45 1 $45
Total Cost $813
The materials were purchased using the UNH Purchasing card program, from which our
project budget was $800.

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Proposed Schedule
Table 2: Proposed Gant Chart
Table 3: Fall Semester Project Schedule
Week of: Tasks:
Oct. 12 – 17  Kickoff meeting
 Review Building Options
Oct. 19 – 23  Meeting w/Kevin O’Maley at Manchester DPW – discuss scope,
building options, introduced to BAS system
 Set up Manchester meetings every Tuesday. 2-3pm
 Narrow building options (Hillside Middle School, McLaughlin
both recommended by DPW)
Oct. 26 – 30  Meeting w/Dr. Bell – Analytical tools, strain gages options
 Set up Thursday meetings 2-3pm
Nov. 2 – 6  Determine budget
 Apply for funds
Nov. 16 – 20  Acquire documents and structural drawings for Hillside Middle
School
Nov. 23 – 27  Design Presentation (CIE)
 Structural Analysis – determine stress/strain range
Nov. 30 – Dec. 4  Design Presentation (ME)
 Structural Analysis & determine type of gages to purchase
Dec. 7 – 11  Order strain gages & amplifier
Dec. 14 – 18  Smart Building Final Paper
Winter Break  When gages delivered, install at school – voltage readings for dead
load
 (Possibly) begin testing at UNH

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Table 4: Spring Semester Project Schedule
Week of: Tasks:
Jan. 26 – 29  Testing at UNH
 Begin modeling in BIM/SAP program
Feb. 1 – 5  Install monitoring system
Feb. 8 – 12  Continue tests on-campus
Feb. 15 – 19  Complete model
Feb. 22 – 26  Lab Tests in Manchester Labs
 Test with BAS System
Feb. 29 – Mar. 4  Continue Manchester testing
Mar. 7 – 11  Data Acquisition & analysis
Mar. 21 – 25  Continue Data Analysis – decide on adjustments if necessary
Mar. 28 – Apr. 1  Make adjustments if needed
Apr. 4 – 8  Gather all data and information necessary for final presentation
 Decision Making Protocol in place
Apr 11 – 15  Final design complete
 Begin finalization of project/presentation

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Strain Gages
The purpose of this project was to analyze, implement, and integrate strain gages into the
Building Automated System (BAS). A strain gages is a device used to measure the strain of a
material or structure at the point of attachment. The Building Automation System does data
acquisition and monitoring. Integrating the strain gage system into the BAS will provide the
DPW with an effective means of monitoring the risk caused by snow loads.
Each strain gage has the same approximate sensitivity. For the purpose of this project, a
quarter bridge was used, which means that there was one sensor that is applied to the beam
vertically along the structural member. A product from OMEGA called a Bridge Completion
Module was used. It provided a means of completing the Wheatstone Bridge circuit that is
necessary for strain gage measurements. The module can be used for quarter bridge
measurements with 120 or 350 Ohm gages or for half bridges with gages of any resistance.
Figure 2: Full Bridge Strain Gage Circuit
Figure 2 shows the configuration of a full bridge strain gage circuit. Accurate results for
strain can be obtained with a full bridge circuit which consists of 4 pre-wired strain gages with
specific orientations. The orientation depends on what type of strain you want to measure. The
full bridge circuit allow for temperature compensation (rates of deformation in the steel due
temperature changes), and has the best sensitivity (the high output to input ratio for stain), but the

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full bridge is also the most intensive to install and requires physically soldering the circuit
yourself. A quarter bridge with one gage is not the most accurate for small scale loads but for
large scale snow loads it will still be effective.
Installation of the final monitoring system will be designed to be capable of lasting at
least twenty years with very minimal maintenance. OMEGA strain gages with model number of
KFH-20-120-C1-11L1M2Rwere used. These are Precision Linear Pattern Pre-Wired Strain
Gages with a nominal resistance of 120 Ohms. The strain gage was attached to the joist by a
suitable adhesive. As the structure deforms, the foil deforms, causing its electrical resistance to
change. This resistance change, was measured using a Wheatstone bridge. The Wheatstone
Bridge is relates the strain the resistance change with gage factor.
 How to Apply Strain Gages
First, the surface of the member was prepped
using an angle grinder with 80 grit sand paper and
then a higher grit emery paper to finish the surface
was used. The surface should not have any grease,
debris, or deep cuts. This is necessary for the
adhesive to correctly bond the strain gage to the
structural member. Figure 3 displays a strain gage
being set up for application.
Next, a cleaning solvent, a mixture of
isopropanol and acetone, is used to degrease, clean,
and wipe off particles from the sanding process. The
beam should not be polished and perfectly smooth
because then it is very difficult for the strain gage to
bond to the structural member. The surface should
still have some small surface scratches.
After completion of surface preparation, use
disposable gloves and tweezers to handle the strain gage. The strain gage should not be touched,
stretched, or compressed, because it will permanently deform the sensor. Now, place the gage in
position on the clean surface. Use cellophane tape to hold the gage in place. Be sure to press out
Figure 3: Strain Gage before the adhesive
is applied

15. 15
all air bubbles between surface and gage. Carefully lift tape with gage adhered bonding side
down, as shown in Figure 3.
Behind the cellophane tape is Teflon tape, this helps prevent gluing your fingers to the
structural member. Apply a thin coat of bonding catalyst to bottom surface of gage. Add a small
amount to the surface. Wait one minute to set the catalyst. BCY01 is an accelerator used for Z70
rapid adhesive. It is an epoxy resin adhesive. To apply the strain gage an adhesive called Z70
was used. Z70 is a rapid adhesive that is a single component cold curing adhesive made of
cyanoacrylate. A layer of gage bonding adhesive was added to the surface. The tape and strain
gage are pressed back down into position on the surface. Smooth the bond and press finger on
the gage to warm the adhesive for two minutes.
Carefully peel the tape back onto itself to remove, leaving the bonded gage adhered to the
surface. Add clear coating over the strain gage. A coating of polyurethane varnish can be applied
to protect the strain gage against moisture. Finally, wrap electrical tape around the strain gage to
protect it from being damaged.
 SignalConditioning: Amplification and Range Matching
The voltage signal from the full bridge strain gage will need to be amplified and
converted into a 0 V to 10 V range. The sensitivities and a thorough analysis will allow for the
conversion into strain, which will be used to calculate the resulting stress. Signal conditioning
means manipulating an analog signal in such a way that it meets the requirements of the next
stage for further processing. Signal conditioning can include amplification, filtering, converting,
range matching, isolation and any other processes that are required to make sensor output
suitable for processing after conditioning. In our case, it will be used to match the range of the
Building Automation System, which requires a 0 – 10 V range. The OMEGA signal conditioner
that was used had a model number of DMD4059, shown in Figure 4.

16. 16
Figure 4: Signal Amplifier that will be used
This amplifier has an adjustable excitation range and it can be mounted using rails. In the school
it is above the ceiling but it is not functional without a permanent power supply. The signal
conditioner is powered with 80 to 265 V AC and it can excite the Wheatstone bridge with 0 to 10
V. The wall outlet was used to power the signal conditioner. With a quarter bridge, an excitation
voltage of 5 V only needed to be supplied to the bridge. The signal conditioner has 4 changeable
options on the side that allows you to amply, range match (modify output range), de-noise,
change excitation voltage, and offset the output. After speaking with OMEGA representatives,
the settings chosen were verified to be correct.
Vulnerable member(s) needed to have functional strain gages installed on them in
Hillside Manchester Middle School. A complete analysis on structural members with and
without snow load was needed to help to determine where to place the strain gage setup.

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Figure 5: Steel Member in Hillside Middle School where sensors will be applied
Figure 5 displays the member that will use the strain gage setup to measure its stress and see
how close it is to yielding. In the BAS, a calculated voltage was used, which correlates to a
strain, in the 0 V to 10 V range that will alert the DPW of concerning stresses in the member
during winter months. From our research and experience, a procedure and foundation that will
enable future implementation by people with little knowledge of the subject was a goal. This
project will provide a means of monitoring the safety of schools in winter months. In addition, in
the long run this project has the potential to save the town of Manchester a rather large amount of
money by implementing the strain gage system into additional schools. If the setup proves to be
reliable over at least twenty years then commercial ventures could also be explored.
Experiments were conducted in the High Bay lab and a room with a press at the
Municipal center in Manchester. These were done to calibrate the gages and calculate sensitivity
from the voltage outputs compared to theoretical outputs. Additional, small scale tests were done
using hanging masses to verify that the output signal was reasonable. The output signal from the
amplifier needed to be calibrated to read zero because strain correlates to the change in strain.
The application of the gage in Hillside Middle School was done on a ladder with safety
glasses, a grinder, and a particle mask. The paint was grinded off the beam and then the beam
was cleaned and prepped. The strain gages were applied, let the adhesive cure and then applied a
varnish to protect the strain gage from moisture. Tests will have to be continued next year by the
next group before it snows in order to zero the signal. The structural member in the school and in
order to calculate the dead load and compare it to the predicted calculation. During the winter the
system should be monitored so ensure that it can be applied for long term application.

18. 18
SAP2000 Modeling
To being the modeling process, we needed to acquire joist dimensions and loading conditions.
JoistDimensions
After Hillside Middle school was decided to be the project location, we then needed to consider
what section of the school would be most susceptible to the largest loading. Wind roses were
analyzed to consider which wing would have the highest snow drifts along with the geometry of
snow loading conditions, which can be seen in Figure 6. The area selected to be analyzed can be
seen in Figure 7 and the joist selected can be seen in Figure 8.
Figure 6: Wind Rose for Manchester, NH

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Figure 7: Location of Interest due to High Snow Loading Conditions
Figure 8: Selected Joist for SAP2000 Analysis

20. 20
From the structural roof framing plans, the joist which would be subject to the loads is a
28LA11. Unfortunately this type of roofing joist was discontinued in the 60’s which is when
Hillside Middle School was constructed (1966). Its physical properties were not listed in the
drawings, nor any steel manual online or from the library. Precise measurements were taken with
calipers and measuring tape at the school. All of these measurements were entered into SAP2000
to recreate joist. The dimensions of the bracing and chords (top and bottom) can be seen in
Figure 9 and Figure 10.
Figure 9: Section Properties of Designed Bracing

21. 21
Figure 10: Section Properties of Designed Top & Bottom Chords
A few views of the joist created in SAP2000 can be seen in Figure 11.
Figure 11: Rendered Views of Joist Created in SAP2000

22. 22
Loading
First, the tributary area needed to be calculated for modeling. The calculation of the internal
joint tributary areas and parameters can be seen below. It should be noted that the tributary areas
for the joint closest to the supports would be ½ of the tributary area of the internal joints.
𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑙 𝐽𝑜𝑖𝑛𝑡 𝑇𝑟𝑖𝑏𝑢𝑡𝑎𝑟𝑦 𝐴𝑟𝑒𝑎 = 𝑆𝑝𝑎𝑐𝑖𝑛𝑔 𝑏𝑒𝑡𝑤𝑒𝑒𝑛 𝑏𝑒𝑎𝑚𝑠 ∗ 𝑆𝑝𝑎𝑐𝑖𝑛𝑔 𝑏𝑒𝑡𝑤𝑒𝑒𝑛 𝑗𝑜𝑖𝑛𝑡𝑠
𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑙 𝐽𝑜𝑖𝑛𝑡 𝑇𝑟𝑖𝑏𝑢𝑡𝑎𝑟𝑦 𝐴𝑟𝑒𝑎 = 3.260167 𝑓𝑡 ∗ 3.862179 𝑓𝑡 = 12.59135 𝑓𝑡2
𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐽𝑜𝑖𝑛𝑡 𝑇𝑟𝑖𝑏𝑢𝑡𝑎𝑟𝑦 𝐴𝑟𝑒𝑎 =
𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑙 𝐽𝑜𝑖𝑛𝑡 𝑇𝑟𝑖𝑏𝑢𝑡𝑎𝑟𝑦 𝐴𝑟𝑒𝑎
2
𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐽𝑜𝑖𝑛𝑡 𝑇𝑟𝑖𝑏𝑢𝑡𝑎𝑟𝑦 𝐴𝑟𝑒𝑎 =
12.59135 𝑓𝑡2
2
= 6.295674 𝑓𝑡2
Deadweight Load
In order to calculate the self-weight of the joist, SAP2000 is capable of computing the
deadweight. The software considers the physical dimensions such as the length, cross-sectional
properties and material properties of A36 steel.
𝐷𝑒𝑎𝑑𝑤𝑒𝑖𝑔ℎ𝑡 = 859.27 𝑙𝑏
Roofing Load
In the structural drawings provided by Manchester the roof dead weight over the selected joist
could be calculated by using cross sectional views and densities of each material found in the
roof.
𝑅𝑜𝑜𝑓 𝐷𝑒𝑎𝑑𝑤𝑒𝑖𝑔ℎ𝑡 = 40 𝑙𝑏/𝑓𝑡2
Snow Load
An appropriate way to calculate approximated snow loads needed to be determined. This is
significant because this is the variable that the system will monitor and New Hampshire’s
weather patterns complicate the calculations.

23. 23
Figure 12: ASCE 7-10 Values for Ground Snow Loads
Notice that in Figure 12, Manchester is in the “CS” (case study) region of the curve. To
calculate snow loads on flat roofs  Pf = 0.7CeCtIPg ASCE Equation (7-1). Pg is found in Figure
12. This creates some ambiguity as to which ground snow load value to use. However, snow
loads aren’t perfectly even, as snow drifts can greatly affect the applied load. ASCE 7-05,
Equation (7-1) will only calculate a flat roof’s distributed weight due to snow. Figure 13 shows
snow loads drifts that need to be considered as the roofing structure will have an irregular snow
load due to the wall of the building. Figure 14 shows the dimensions of this snow drift geometry
that are used in calculation of snow loads using ASCE 7-10.
Figure 13: Drifts Formed at Windward and Leeward Steps

24. 24
Figure 14: Configuration of Snow Drifts on Lower Roofs
It is important to think about the density of the snow. Snow can be light, or after a
rainstorm, extremely heavy. ASCE 7-10 provides a connection between snow loads on flat roofs
and the density of drifted snow on a roof, Ƴ = 0.13Pg + 14, Equation (7-3).
The below calculations use dimensions highlighted in Figure 14. These measurements
were taken in field to ensure high accuracy. With the structural drawings being extremely old
and faded, at times they were tough to read clearly. With the importance of the loading
conditions in this project, it was concluded that measurements should be taken in the field rather
than trying to decipher old drawings.
Figure 15: ASCE 7-10 Snow Load Calculation

25. 25
The above calculations conclude that the joist will be exposed to a maximum drift load of 111
lbs/ft2 and a distributed balanced snow load of 54 lbs/ft2.
ModelAnalysis
After creating the joist in SAP2000 and calculating the loading conditions, SAP2000 was then
again used to perform a structural analysis. This analysis yielded the stress in all of the members
of the truss. It was decided by Kevin that he wanted to be alarmed when the loading conditions
are nearing 60% of the yield strength. This is because once steel surpasses its yield strength,
linear elastic behavior will no longer exist. For A36 → Fy = 36 ksi, consequently, 0.6Fy = 21.6
ksi The corresponding strains to these stresses are 0.001241 in/in & 0.000757 in/in respectively.
The predicted stress distribution due to snow loads can be seen in Figure 16 and the predicted
exaggerated deformation due to the snow loads can be seen in Figure 17.
Figure 16: Predicted Stress Distribution due to Snow Loads
Figure 17: Predicted Deformation due to Snow Loads
With the assumption of Hooke’s Law all of the expected strains could be calculated in these
members using the modulus of elasticity, 29000 ksi for A36 steel. These calculations can be
seen in Table 5 and a graphical representation can be seen on Figure 18.

26. 26
Table 5: Summary of Strain Calculations from SAP2000
Figure 18: Graphical Representation of Strain Calculation in Comparison to 60% of Yielding
Strain
Using this information the most vulnerable member was found to be on the bottom chord, 6th
division in from the left support, which can be seen in Figure 19.
DEAD LOAD STRAIN
Our straingauge willbe
zeroed at the calculated
strain due to the dead
loads (roofing& joist)
since the straingauge
onlypicks upchanges in
strain.
SNOW LOAD STRAIN
This is the calculated
strain due to the
maximum designsnow
loadbasedoffof ASCE 7-
10.
TOTAL LOAD STRAIN
This is the totalcalculated
strain due to the snow
loadanddeadloads.
STRAIN AT 60% Fy
This straincorrelates to
the 10 volt reading inthe
BAS system.
0
5
10
15
20
25
0 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006 0.0007 0.0008
Stress(ksi)
Strain (in/in)

27. 27
Figure 19: Location of Vulnerable Member
An additional analysis was run with point loads from 100 lbs to 1000 lbs over the most
vulnerable joint. This was done to calculate expected strains which will be used to compare to
field test results after the system is installed. This will help ensure that the systems behavior is
matching with what the expected results would be. The summary of the strain due to this loading
can be seen in Table 6 below.
Table 6: Predicted Strain due to Incrimental 100 lb Loading
Using the data above, the predicted strain for 320 lbs could be determined since these values are
in the linear elastic region, which was calculated to be 0.0000270345 in/in. Single person
predicted strain was also determined to obtain more data entries to compare to field testing.
These values determined through the model was 0.0000093793 in/in for 170 lb and
0.0000176552 in/in for 160 lbs. The predicted stress distribution due to this loading can be seen
in Figure 20.
Figure 20: Predicted Stress Distribution due to 320 lbs

28. 28
Data Analysis
Preliminary Testing at UNH
Before the strain gauge and signal amplifier were installed at Hillside Middle School,
small scale testing was performed on a steel flat bar. The strain gauge was installed on the center
of the flat bar along the bottom-facing surface. The bridge module and signal conditioner were
connected to this strain gauge similar to the final setup.
Several hanging weights with known masses were hung from the center of the flat bar,
and for each added mass, the change in voltage was read using a voltmeter. Readings were taken
directly from the voltage drop across the bridge module as well as from the output of the signal
conditioner.
Figure 21: Force v. Voltage plots of preliminary testing of strain gauge set up on flat bar; a)
Voltage read from the bridge module, b) Voltage read from signal conditioner, c) relationship
between voltage readings from the Bridge Module and the Signal Conditioner

29. 29
These tests allowed us to confirm that our equipment was set up correctly. As masses
were added to the hanger, the voltage increased proportionally to the increase in weight. This
validated that the strain gauge was responding correctly to an increase in stress within the Elastic
Region.
Plot C in Figure 21 above also shows that there is a linear relationship between the
voltage across the bridge module and the output voltage from the signal conditioner. This further
confirms that our setup will correctly read the strain gauge and convert that signal to the 0-10
volt range required by the Building Automation System.
On-Site Testing at Hillside Middle School
Some testing was also completed at Hillside Middle School once the strain gauge and the
rest of the system was installed.
Figure 22: Strain measurements from testing at Hillside Middle School vs. Strain values from
SAP2000 model
The test was executed by adding known weight on top of the roof over the spot where the
strain gauge had been installed. In this instance, the masses were body weight from team
members standing in the designated spot on the roof. The voltage was read using a voltmeter
connected to the output of the signal conditioner. This voltage was then converted to strain.
0
50
100
150
200
250
300
350
0 0.000005 0.00001 0.000015 0.00002 0.000025
Mass(lb)
Strain (in/in)
Strain Measurments Model vs. Emperical Data
Model Strain
Experimental Strain

30. 30
As with the testing in the UNH lab, a change increase in voltage as the stress on the roof
increased was seen. However, limitations in the test methodology led to a significant error
between the model strain and the empirical data.
The model used to calculate strain values could have been calibrated incorrectly,
contributing to the error. The voltmeter used to obtain strain measurements also had a lot of
noise, which also complicated the retrieval of accurate voltage readings. These factors have been
the main contributors to the error in our calculated experimental strain values in comparison to
the model calculated values.

31. 31
Closing Comments
Future Work
According to our model and theoretical stipulations, it can be concluded that the integrity
of the monitored joist will not be compromised, using the maximum case study snow loads as an
estimation. This project has laid the foundation for further study and optimization of this system
for the Building Automation System.
In order to wholly justify these theoretical results, however, more empirical data must be
collected. It is recommended that live snow-load data should be obtained during the coming
winter to allow the system to analyze data and present opportunities for optimization. The scope
of this project in the future should primarily focus on expanding the system to include multiple
strain gages networked into the same interface so that data for each gage can be monitored. A
network of gages will result in a more accurate depiction of risk and allow the BAS to monitor
the entire bay where the vulnerable joist is located. It is also important that the model is updated
to include the entire bay as well, in order to get a more accurate depiction the effects of
maximum stress in different locations along this section of the roof.
A suggestion for this system’s further use is that if this system is going to be used and
expanded upon next year that the future group considers a platform other than OMEGA.
National Instruments (NI) is utilized at the UNH High Bay lab. This platform allows for the
acquisition of data for a network of strain gages (up to 6). An additional benefit is that the strain
gages can be hooked up directly to the NI data acquisition module, which would eliminate the
need for the bridge module and the signal conditioner. The inclusion of all the components in a
single unit will allow for easier installation and the additional housing could also ensure a more
durable final product. Utilizing the NI system will also make testing at UNH and testing on-site
easier and simplify comparisons between the two. The disadvantage of this platform, however, is
that it is not primarily designed for continuous data acquisition and monitoring, which is required
for this application. It may be beneficial for a future group research this platform to determine if
it can be manipulated for continuous monitoring, because it will allow for easier installation and
provide a more reliable set up.

32. 32
Since snow loads can be somewhat unpredictable due to varying snow density, acquiring
data in real-time during winter will enable future groups to better approximate snow loads during
calculations and within the model.
Recommendations for Future Groups
The division of tasks for this project was decided using a responsibility assignment
matrix, or RACI chart, Table 7. This type of chart is particularly useful in delegating roles and
responsibilities for inter-department projects. The project was sub-divided into four larger
concepts that must be achieved: the structural analysis of the roof, design testing (on-campus as
well as at the Manchester Department of Public Works), data acquisition and initial
implementation of the design, and creation of the decision making protocol for the Building
Automation System. For each of these categories, every project member was assigned a different
level of involvement (Responsible, Accountable, Consulted, or Informed). These levels are
defined as follows:
Responsible: does the work to make sure task is completed, though when necessary other
members may assist in the work required
Accountable: is answerable for the completion of the task/the final approving authority;
person must sign off work that Responsible member provides.
Consulted: advisee for members mentioned above; Two-way conversation had in order
to gain further knowledge or outside perspective on the task.
Informed: is kept up-to-date on task progress, and notified upon completion of the task.
Table 7: RACI Chart
Structural
Analysis
Design
Testing
Data
Acquisition
Decision
Protocol
Brad
Casperson
A R C I
Mike
Langelier
I A R C
Jasmine
Seguin
C I A R

33. 33
Ryan
Vickers
R C I A
While initially we found this chart helpful, the segregation of important tasks also led to a
gap in communications which was particularly difficult when complications arose with the
electrical components. For future groups, we suggest this type of chart only for a larger group. It
is recommended having a larger number of group members in the future, between 6-8 group
members. This will all enable groups to break into smaller groups so that multiple systems can
be installed simultaneously in different locations. Also, since the work involved will be split
between Manchester and the UNH campus in Durham, having more members would allow the
group to be more readily split between these locations when necessary. It is also suggested that
group members from the engineering programs at the UNH Manchester campus be involved in
this project. The RACI chart is also only helpful when a strict meeting schedule is put in place,
allowing all members the chance to update other parts of the team often.
For this project, weekly meetings were planned to meet in Manchester at the DPW
offices as well as with advisors, if necessary, on separate days. These meetings were utilized to
discuss the project timeline, acquire research and needed documents (such as the building plans),
and to keep all team members, faculty advisors, and the DPW up to date with the project’s
progress. However, scheduling conflicts and time constraints made it difficult to keep this
schedule strictly.
The largest difficulty, we have found, in having an inter-disciplinary project with
components both in Manchester and at UNH has been scheduling conflicts which make it
difficult for all members to be present at every meeting. In order to make up for everyone having
different schedules numerous meetings were held a week, in addition to the multiple emails and
instant messages that were sent through Facebook. If a member missed a meeting it was easy to
fill them in but in order for progress and a cohesive and unite team, it was much preferred to
have everyone at a meeting. During this project, because it was difficult to get all members
present for many meetings, it was difficult to keep the entire team on the same page.
This also led to fragmented communications across the board. Communication was the
key factor for success for this group, and our experience leads us to suggest having a
comprehensive plan in place at the start of the group in order to make up for the difficulties in a

34. 34
having an interdisciplinary group that also has key people and components of the project split
between several locations. A wider use of programs like Skype or other means of online
meetings is something be taken in consideration. These may be more time and resource effective,
especially to show or discuss models and testing setups that are not portable. This will also allow
for everyone to be present at meetings even if that cannot travel. It is also heavily suggested that
team members contact faculty and graduate students in charge of laboratories or equipment that
may be needed during the time span of the project and time set up before the lab or equipment is
necessary. Meeting with persons in charge of the labs will not only create a wider network of
resources for the project, but it will allow them to become familiar with the project so that they
may provide assistance as required more efficiently.
Additionally, by including a team member with a comprehensive electrical engineering
background will allow the project to progress more quickly. Having a team member who has a
greater familiarity with troubleshooting electronic systems will make it easier for the group to
identify subtler or more serious problems that may occur in the electrical components of the
system.
One of our most important recommendations is that future team members meet with the
Principal and other important members of the school in which they will be conducting work. Our
group did not have a formal meeting with Hillside Middle School before work began on-site,
which meant that when we showed up without a member of the Department of Public Works, it
was difficult to get access to the classroom where the joist was located. Meeting with the school
officials early will keep them in the loop and facilitate on-site work. Keeping the school
informed about the project and the progress being made will allow a greater freedom to schedule
time to work at the site (without necessarily needing a member of the DPW). Another benefit of
establishing a stronger relationship with the school at the start of the project is the opportunity
for a STEM outreach program that would inform and include students in the project and
introducing them to the engineering principals relevant to the work being done.
The previous recommendation will also ensure a safer working environment, since work
is often done after school ours, and the work space offers several concerns. One of the major
trepidations with working above the ceiling panels is the difficulty in reaching the parts of the
joist that are of interest. A ladder can typically be found on-site; however, it is not recommended
that any persons work on-site without another team member there. A flashlight is also necessary

35. 35
since there is not sufficient lighting from the classroom. There is also a concern due to the
amount of dust in the work space above the ceiling tiles. Because grinding is necessary for strain
gage installation, caution must be taken since the sparks initiated from the grinder are potentially
flammable.
It is our hope that these recommendations and notes for the progress that needs to be
made will assist future team members in more effectively creating a comprehensive plan to
improve the ground work that we have provided in this report.