It is necessary to design a bed packed with rectangular glass prisms that measure 1 cm and 2 cm high with a sphericity of 0.72, which will be used as a support to purify air that enters a gauge pressure of 2 atm and 40 ° C. The density of the prisms is 1300 kg/m^3 and 200 kg is used to pack the column. The column is a polycarbonate tube with a diameter of 0.3 and a height of 3.5 m. considering that the feed is 3kg/min and the height of the fluidized bed is 2.5 m. Determine the gauge pressure at which the air leaves, in atm.

Answers

Answer 1

To determine the gauge pressure at which the air leaves the bed, we need to consider the pressure drop across the packed bed of glass prisms.

The pressure drop is caused by the resistance to airflow through the bed. First, let's calculate the pressure drop due to the weight of the glass prisms in the bed:

1. Determine the volume of the glass prisms:

  - Volume = (area of prism base) x (height of prism) x (number of prisms)

  - Area of prism base = (length of prism) x (width of prism)

  - Number of prisms = mass of prisms / (density of prisms x volume of one prism)

2. Calculate the weight of the glass prisms:

  - Weight = mass of prisms x g

3. Calculate the pressure drop due to the weight of the prisms:

  - Pressure drop = (Weight / area of column cross-section) / (height of fluidized bed)

Next, we need to consider the pressure drop due to the resistance to airflow through the bed. This can be estimated using empirical correlations or experimental data specific to the type of packing being used.

Finally, the gauge pressure at which the air leaves the bed can be determined by subtracting the calculated pressure drop from the gauge pressure at the inlet.

Please note that accurate calculations for pressure drop in packed beds often require detailed knowledge of the bed geometry, fluid properties, and packing characteristics.

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Related Questions

Considering the above scenario, the engineer should make a report/presentation explaining the process of design on different component and its manufacturing; finally, an integration as a complete system. (Process of VR design (constraints and criteria), components of manufacturing a fountain including audio system and lights display and any other auxiliary (fire-works display, multiple screen and advertising screens)

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For the process of VR design, the engineer should start by considering the constraints and criteria. The engineer should first consider the specific requirements of the client in terms of the design of the fountain. The constraints may include the size of the fountain, the materials that will be used, and the budget that the client has allocated for the project.



After considering the constraints and criteria, the engineer should start designing the fountain using virtual reality technology. Virtual reality technology allows engineers to design complex systems such as fountains with great accuracy and attention to detail. The engineer should be able to create a virtual model of the fountain that incorporates all the components that will be used in its manufacture, including the audio system and the lights display.

Once the design is complete, the engineer should then proceed to manufacture the fountain. The manufacturing process will depend on the materials that have been chosen for the fountain. The engineer should ensure that all the components are of high quality and meet the specifications of the client.

Finally, the engineer should integrate all the components to create a complete system. This will involve connecting the audio system, the lights display, and any other auxiliary components such as fireworks displays and multiple screens. The engineer should also ensure that the fountain meets all safety and regulatory requirements.

In conclusion, the engineer should prepare a report or presentation that explains the process of designing and manufacturing the fountain, including all the components and the integration process. The report should also highlight any challenges that were encountered during the project and how they were overcome. The engineer should also provide recommendations for future improvements to the design and manufacturing process.

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Determine the design heating load for a residence, 30 by 100 by 10 ft (height), to be located in Windsor Locks, Connecticut (design indoor temperature is 72 F and 30% RH and outdoor temperature is 3 F and 100% RH), which has an uninsulated slab on grade concrete floor (F-0.84 Btu/ft). The construction consists of Walls: 4 in. face brick (R=0.17), % in plywood sheathing (R=0.93), 4 in. cellular glass insulation (R=12.12), and / in. plasterboard (R=0.45) Ceiling/roof: 3 in. lightweight concrete deck (R=0.42), built-up roofing (R=0.33), 2 in. of rigid, expanded rubber insulation (R=9.10), and a drop ceiling of 7 in, acoustical tiles (R=1.25), air gap between rubber insulation and acoustical tiles (R=1.22) Windows: 45% of each wall is double pane, nonoperable, metal-framed glass with 1/4 in, air gap (U-0.69) Doors: Two 3 ft by 7 A, 1.75 in. thick, solid wood doors are located in each wall (U-0.46) All R values are in hr ft F/Btu and U values are in Btu/hr ft F units. R=1/U.

Answers

Design Heating Load Calculation for a residence located in Windsor Locks, Connecticut with an uninsulated slab on grade concrete floor and different construction materials is given below: The heating load is calculated by using the formula:

Heating Load = U × A × ΔTWhere,U = U-value of wall, roof, windows, doors etc.A = Total area of the building, walls, windows, roof and doors, etc.ΔT = Temperature difference between inside and outside of the building. And a drop ceiling of 7 in,

acoustical tiles (R = 1.25)Air gap between rubber insulation and acoustical tiles (R = 1.22)The area of the ceiling/roof, A = L × W = 3000 sq ftTherefore, heating load for ceiling/roof = U × A × ΔT= 0.0813 × 3000 × (72 - 3)= 17973 BTU/hrWalls:4 in.

face brick (R = 0.17)0.5 in. plywood sheathing (R = 0.93)4 in. cellular glass insulation (R = 12.12)And 0.625 in. Therefore, heating load for walls = U × A × ΔT= 0.0731 × 5830 × (72 - 3)= 24315 BTU/hrWindows:

45% of each wall is double pane, nonoperable, metal-framed glass with 1/4 in. air gap (U = 0.69)Therefore, heating load for doors = U × A × ΔT= 0.46 × 196 × (72 - 3)= 4047 BTU/hrFloor:

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The open-loop transfer function of a unit-negative-feedback system has the form of
G(s)H(s) = 1 / s(s+1).
Please determine the following transient specifications when the reference input is a unit step function:
(1) Percentage overshoot σ%;
(2) Peak time tp;
(3) 2% Settling time t.

Answers

For the given open-loop transfer function 1 / (s(s+1)), the transient specifications when the reference input is a unit step function can be determined by calculating the percentage overshoot, peak time, and 2% settling time using appropriate formulas for a second-order system.

What is the percentage overshoot?

To determine the transient specifications for the given open-loop transfer function G(s)H(s) = 1 / (s(s+1)) with a unit step reference input, we need to analyze the corresponding closed-loop system.

1) Percentage overshoot (σ%):

The percentage overshoot is a measure of how much the response exceeds the final steady-state value. For a second-order system like this, the percentage overshoot can be approximated using the formula: σ% ≈ exp((-ζπ) / √(1-ζ^2)) * 100, where ζ is the damping ratio. In this case, ζ = 1 / (2√2), so substituting this value into the formula will give the percentage overshoot.

2) Peak time (tp):

The peak time is the time it takes for the response to reach its maximum value. For a second-order system, the peak time can be approximated using the formula: tp ≈ π / (ωd√(1-ζ^2)), where ωd is the undamped natural frequency. In this case, ωd = 1, so substituting this value into the formula will give the peak time.

3) 2% settling time (ts):

The settling time is the time it takes for the response to reach and stay within 2% of the final steady-state value. For a second-order system, the settling time can be approximated using the formula: ts ≈ 4 / (ζωn), where ωn is the natural frequency. In this case, ωn = 1, so substituting this value into the formula will give the 2% settling time.

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deposited uniformly on the Silicon(Si) substrate, which is 500um thick, at a temperature of 50°C. The thermal elastic properties of the film are: elastic modulus, E=EAI=70GPa, Poisson's ratio, VFVA=0.33, and coefficient of thermal expansion, a FaA=23*10-6°C. The corresponding Properties of the Si substrate are: E=Es=181GpA and as=0?i=3*10-6°C. The film-substrate is stress free at the deposition temperature. Determine a) the thermal mismatch strain difference in thermal strain), of the film with respect to the substrate(ezubstrate – e fim) at room temperature, that is, at 20°C, b)the stress in the film due to temperature change, (the thickness of the thin film is much less than the thickness of the substrate) and c)the radius of curvature of the substrate (use Stoney formula)

Answers

Determination of thermal mismatch strain difference Let's first write down the given values: Ea1 = 70 GP a (elastic modulus of film) Vf1 = 0.33 (Poisson's ratio of film)α1 = 23 × 10⁻⁶/°C (coefficient of thermal expansion of film).

Es = 181 GP a (elastic modulus of substrate)αs = 3 × 10⁻⁶/°C (coefficient of thermal expansion of substrate)δT = 50 - 20 = 30 °C (change in temperature)The strain in the film, due to temperature change, is given asε1 = α1 × δT = 23 × 10⁻⁶ × 30 = 0.00069The strain in the substrate, due to temperature change, is given asεs = αs × δT = 3 × 10⁻⁶ × 30 = 0.00009.

Therefore, the thermal mismatch strain difference in thermal strain), of the film with respect to the substrate(ezubstrate – e film) at room temperature, that is, at 20°C is 0.0006. Calculation of stress in the film due to temperature change Let's calculate the stress in the film due to temperature change.

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b) Determine the 4-point Discrete Fourier Transform (DFT) of the below function: x(n)={ 0
1

(n=0,3)
(n=1,2)

Find the magnitude of the DFT spectrum, and sketch the result. (10 marks)

Answers

The correct answer is "The 4-point DFT of the given function is x(0)=2, x(1)=0, x(2)=0, and x(3)=0. The magnitude of the DFT spectrum is 2, 0, 0, 0. The graph of the magnitude of the DFT spectrum is as shown above."

The given function is;x(n)={ 0 1
​(n=0,3)
(n=1,2)
​The formula for Discrete Fourier Transform (DFT) is given by;

x(k)=∑n

=0N−1x(n)e−i2πkn/N

Where;

N is the number of sample points,

k is the frequency point,

x(n) is the discrete-time signal, and

e^(-i2πkn/N) is the complex sinusoidal component which rotates once for every N samples.

Substituting the given values in the above formula, we get the 4-point DFT as follows;

x(0) = 0+1+0+1

=2

x(1) = 0+j-0-j

=0

x(2) = 0+1-0+(-1)

= 0

x(3) = 0-j-0+j

= 0

The DFT spectrum for 4-point DFT is given as;

x(k)=∑n

=0

N−1x(n)e−i2πkn/N

So, x(0)=2,

x(1)=0,

x(2)=0, and

x(3)=0

As we know that the magnitude of a complex number x is given by

|x| = sqrt(Re(x)^2 + Im(x)^2)

So, the magnitude of the DFT spectrum is given as;

|x(0)| = |2|

= 2|

x(1)| = |0|

= 0

|x(2)| = |0|

= 0

|x(3)| = |0| = 0

Hence, the magnitude of the DFT spectrum is 2, 0, 0, 0 as we calculated above. Also, the graph of the magnitude of the DFT spectrum is as follows:
Therefore, the correct answer is "The 4-point DFT of the given function is x(0)=2, x(1)=0, x(2)=0, and x(3)=0. The magnitude of the DFT spectrum is 2, 0, 0, 0. The graph of the magnitude of the DFT spectrum is as shown above."

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Design a excel file of an hydropower turgo turbine in Sizing and Material selection.
Excel file must calculate the velocity of the nozel, diameter of the nozel jet, nozzle angle, the runner size of the turgo turbine, turbine blade size, hub size, fastner, angular velocity,efficiency,generator selection,frequnecy,flowrate, head and etc.
(Note: File must be in execl file with clearly formulars typed with all descriptions in the sheet)

Answers

Designing an excel file for a hydropower turbine (Turgo turbine) involves calculating different values that are essential for its operation. These values include the velocity of the nozzle, diameter of the nozzle jet, nozzle angle, runner size of the turbine, turbine blade size, hub size, fastener, angular velocity, efficiency, generator selection, frequency, flow rate, head, etc.

To create an excel file for a hydropower turbine, follow these steps:Step 1: Open Microsoft Excel and create a new workbook.Step 2: Add different sheets to the workbook. One sheet can be used for calculations, while the others can be used for data input, output, and charts.Step 3: On the calculation sheet, enter the formulas for calculating different values. For instance, the formula for calculating the velocity of the nozzle can be given as:V = (2 * g * H) / (√(1 - sin²(θ / 2)))Where V is the velocity of the nozzle, g is the acceleration due to gravity, H is the head, θ is the nozzle angle.Step 4: After entering the formula, label each column and row accordingly. For example, the velocity of the nozzle formula can be labeled under column A and given a name, such as "Nozzle Velocity Formula".Step 5: Add a description for each formula entered in the sheet.

The explanation should be clear, concise, and easy to understand. For example, a description for the nozzle velocity formula can be given as: "This formula is used to calculate the velocity of the nozzle in a hydropower turbine. It takes into account the head, nozzle angle, and acceleration due to gravity."Step 6: Repeat the same process for other values that need to be calculated. For example, the formula for calculating the diameter of the nozzle jet can be given as:d = (Q / V) * 4 / πWhere d is the diameter of the nozzle jet, Q is the flow rate, and V is the velocity of the nozzle. The formula should be labeled, given a name, and described accordingly.Step 7: Once all the formulas have been entered, use the data input sheet to enter the required data for calculation. For example, the data input sheet can contain fields for flow rate, head, nozzle angle, etc.Step 8: Finally, use the data output sheet to display the calculated values. You can also use charts to display the data graphically. For instance, you can use a pie chart to display the percentage efficiency of the turbine. All the sheets should be linked correctly to ensure that the data input reflects on the calculation sheet and output sheet.

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Compute the Fourier Series decomposition of a square waveform with 90% duty cycle

Answers

The Fourier series decomposition of the square waveform with a 90% duty cycle is given by: f(t) = (a0/2) + ∑[(an * cos((2πnt)/T)) + (bn * sin((2πnt)/T))]

The Fourier series decomposition for a square waveform with a 90% duty cycle:

Definition of the Square Waveform:

The square waveform with a 90% duty cycle is defined as follows:

For 0 ≤ t < T0.9 (90% of the period), the waveform is equal to +1.

For T0.9 ≤ t < T (10% of the period), the waveform is equal to -1.

Here, T represents the period of the waveform.

Fourier Series Coefficients:

The Fourier series coefficients for this waveform can be computed using the following formulas:

a0 = (1/T) ∫[0 to T] f(t) dt

an = (2/T) ∫[0 to T] f(t) cos((2πnt)/T) dt

bn = (2/T) ∫[0 to T] f(t) sin((2πnt)/T) dt

where a0, an, and bn are the Fourier coefficients.

Computation of Fourier Coefficients:

For the given square waveform with a 90% duty cycle, we have:

a0 = (1/T) ∫[0 to T] f(t) dt = 0 (since the waveform is symmetric around 0)

an = 0 for all n ≠ 0 (since the waveform is symmetric and does not have cosine terms)

bn = (2/T) ∫[0 to T] f(t) sin((2πnt)/T) dt

Computation of bn for n = 1:

We need to compute bn for n = 1 using the formula:

bn = (2/T) ∫[0 to T] f(t) sin((2πt)/T) dt

Breaking the integral into two parts (corresponding to the two regions of the waveform), we have:

bn = (2/T) [∫[0 to T0.9] sin((2πt)/T) dt - ∫[T0.9 to T] sin((2πt)/T) dt]

Evaluating the integrals, we get:

bn = (2/T) [(-T0.9/2π) cos((2πt)/T)] from 0 to T0.9 - (-T0.1/2π) cos((2πt)/T)] from T0.9 to T

bn = (2/T) [(T - T0.9)/2π - (-T0.9)/2π]

bn = (T - T0.9)/π

Fourier Series Decomposition:

The Fourier series decomposition of the square waveform with a 90% duty cycle is given by:

f(t) = (a0/2) + ∑[(an * cos((2πnt)/T)) + (bn * sin((2πnt)/T))]

However, since a0 and an are 0 for this waveform, the decomposition simplifies to:

f(t) = ∑[(bn * sin((2πnt)/T))]

For n = 1, the decomposition becomes:

f(t) = (T - T0.9)/π * sin((2πt)/T)

This represents the Fourier series decomposition of the square waveform with a 90% duty cycle, including the computation of the Fourier coefficients and the final decomposition expression for the waveform.

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