EBK NUMERICAL METHODS FOR ENGINEERS
7th Edition
ISBN: 9780100254145
Author: Chapra
Publisher: YUZU
expand_more
expand_more
format_list_bulleted
Textbook Question
Chapter 20, Problem 33P
The following model is frequently used in environmental engineering to parameterize the effect of temperature T(°C) on biochemical reaction rates k (per day),
where
|
6 | 12 | 18 | 24 | 30 |
|
0.14 | 0.20 | 0.31 | 0.46 | 0.69 |
Expert Solution & Answer
![Check Mark](/static/check-mark.png)
Want to see the full answer?
Check out a sample textbook solution![Blurred answer](/static/blurred-answer.jpg)
Students have asked these similar questions
As an industrial engineer, you intend to use linear trend (or linear regression) method to solve a forecasting problem. You have decided to use the equation of y = m(x) + c to establish the relationship between the sales (y) and the related month (x). It is known that 8 consecutive months data (Jan to Aug) were used and they resulted to the following parameter values of m = 320 and c = 1017. Using the regression technique, estimate the percentage of sales improvement from December this year to June next year.
4. Given the following data :
T(k')
600
700
800
900
(Cp/R)
3.671
3.755
3.838
3.917
Where "T" is the absolute temperature and (C,/R) is the dimensionless specific heat of
air. Use Newton's forward interpolation method to find the specific heat at T = 670 k°.
%3D
The following table lists temperatures and specific volumes of water vapor at
two pressures:
p = 1.5 MPa
v(m³/kg)
p = 1.0 MPa
T ("C)
v(m³/kg)
T ("C)
200
0.2060
200
0.1325
240
280
0.2275
0.2480
240
280
0.1483
0.1627
Data encountered in solving problems often do not fall exactly on the grid of
values provided by property tables, and linear interpolation between adjacent
table entries becomes necessary. Using the data provided here, estimate
i. the specific volume at T= 240 °Č, p = 1.25 MPa, in m/kg
ii. the temperature at p = 1.5 MPa, v = 0.1555 m/kg, in °C
ii. the specific volume at T = 220 °C, p = 1.4 MPa, in m'/kg
Chapter 20 Solutions
EBK NUMERICAL METHODS FOR ENGINEERS
Ch. 20 - 20.1 Perform the same computation as in Sec. 20.1,...Ch. 20 - You perform experiments and determine the...Ch. 20 - 20.3 It is known that the tensile strength of a...Ch. 20 - Prob. 4PCh. 20 - 20.5 The specific volume of a superheated steam is...Ch. 20 - Prob. 6PCh. 20 - In Alzheimers disease, the number of neurons in...Ch. 20 - 20.8 The following data were taken from a stirred...Ch. 20 - Prob. 9PCh. 20 - Concentration data were taken at 15 time points...
Ch. 20 - Prob. 11PCh. 20 - The molecular weight of a polymer can be...Ch. 20 - 20.13 On average, the surface area A of human...Ch. 20 - 20.14 Determine an equation to predict metabolism...Ch. 20 - 20.15 Human blood behaves as a Newtonian fluid...Ch. 20 - 20.16 Soft tissue follows an exponential...Ch. 20 - 20.17 The thickness of the retina changes during...Ch. 20 - 20.18 The data tabulated below were generated from...Ch. 20 - The shear stresses, in kilopascals (kPa), of nine...Ch. 20 - 20.20 A transportation engineering study was...Ch. 20 - The saturation concentration of dissolved oxygen...Ch. 20 - For the data in Table P20.21, use polynomial...Ch. 20 - 20.23 Use multiple linear regression to derive a...Ch. 20 - 20.24 As compared to the models from Probs. 20.22...Ch. 20 - 20.25 In water-resources engineering, the sizing...Ch. 20 - 20.26 The concentration of total phosphorus and...Ch. 20 - 20.27 The vertical stress under the corner of a...Ch. 20 - Three disease-carrying organisms decay...Ch. 20 - 20.29 The mast of a sailboat has a cross-sectional...Ch. 20 - 20.30 Enzymatic reactions are used extensively to...Ch. 20 - 20.31 Environmental engineers dealing with the...Ch. 20 - An environmental engineer has reported the data...Ch. 20 - The following model is frequently used in...Ch. 20 - 20.34 As a member of Engineers Without Borders,...Ch. 20 - 20.35 Perform the same computations as in Sec....Ch. 20 - 20.36 You measure the voltage drop V across a...Ch. 20 - Duplicate the computation for Prob. 20.36, but use...Ch. 20 - The current in a wire is measured with great...Ch. 20 - 20.39 The following data was taken from an...Ch. 20 - It is known that the voltage drop across an...Ch. 20 - Ohms law states that the voltage drop V across an...Ch. 20 - 20.42 Repeat Prob. 20.41 but determine the...Ch. 20 - 20.43 An experiment is performed to determine the...Ch. 20 - Bessel functions often arise in advanced...Ch. 20 - 20.45 The population of a small community on the...Ch. 20 - Based on Table 20.4, use linear and quadratic...Ch. 20 - 20.47 Reproduce Sec. 20.4, but develop an equation...Ch. 20 - 20.48 Dynamic viscosity of water is related to...Ch. 20 - 20.49 Hooke’s law, which holds when a spring is...Ch. 20 - 20.50 Repeat Prob. 20.49 but fit a power curve to...Ch. 20 - The distance required to stop an automobile...Ch. 20 - An experiment is performed to define the...Ch. 20 - The acceleration due to gravity at an altitude y...Ch. 20 - The creep rate is the time rate at which strain...Ch. 20 - 20.55 It is a common practice when examining a...Ch. 20 - The relationship between stress and the shear...Ch. 20 - The velocity u of air flowing past a flat surface...Ch. 20 - 20.58 Andrade’s equation has been proposed as a...Ch. 20 - Develop equations to fit the ideal specific heats...Ch. 20 - 20.60 Temperatures are measured at various points...Ch. 20 - 20.61 The data below were obtained from a creep...
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, mechanical-engineering and related others by exploring similar questions and additional content below.Similar questions
- 4 Discharge, Q through a venturimeter depends on the following variable Inlet pipe diameter - D Throat diameter - d Pressure drop across the venturimeter - Ap Fluid density - P Dynamic viscosity - µ Using MLT set of dimensions evaluate the dimensionless parameters correlating this phenomenon 5 The droplet size, D produced by a liquid spray nozzle depends on the following variable Nozzle diameter - d Jet velocity - U Fluid density - p Dynamic viscosity – u Surface tension - o Using MLT set of dimensions evaluate the dimensionless parameters correlating this phenomenonarrow_forwardThe population P in thousands of Tallahassee, Florida, from 2000 through 2014 can be modeled by P = 150.9ekt, where t represents the year, with t = 0 corresponding to 2000. In 2005, the population of Tallahassee was about 163,075.(a) Find the value of k. Is the population increasing or decreasing? Explain. (b) Use the model to predict the populations of Tallahassee in 2020 and 2025. Are the results reasonable? Explain. (c) According to the model, during what year will the population reach 200,000?arrow_forwardFrom Newton, we have that the equation that best fits the linear regression of a graph of tension vs acceleration is: y = 0.694x + 0.23 if we know that the mass of the cart (M) is 600 grains, how much would the mass be pendant (m)arrow_forward
- A sphere is moving in water with a velocity of 1.6 m/s. Another sphere of twice the diameter is placed in a wind tunnel and tested with air which is 750 times less dense and 60 times less viscous (dynamically) than water. The velocity of air that will model dynamically similar conditions isarrow_forwardQ=What is the importance of regression analysis in transportation engineering? ANSWER in word fomatarrow_forwardFor the Thermistor given below using piecewise approximation method combined with line regression to find the best equation and value for Temperature if the system has counts =800 20 40 60 80 |ADC counts 928 785 654 420 152 T=129.7902-0.14586*Counts, T= 13.1022 T=129.7902-0.13986*Counts, T=17.9021 T=129.7902-0.12358*Counts, T= 30.9262 T=135.4745-0.14599*Counts, T= 18.68613arrow_forward
- Cardiologists use the short-range scaling exponent α1, which measures the randomness of heart rate patterns, as a tool to assess risk of heart attack. The article “Applying Fractal Analysis to Short Sets of Heart Rate Variability Data” compared values of α1 computed from long series of measurements (approximately 40,000 heartbeats) with those estimated from the first 300 beats to determine how well the long-term measurement (y) could be predicted the short-term one (x). Following are the data (obtained by digitizing a graph). Short Long 0.54 0.55 1.02 0.79 1.4 0.81 0.88 0.9 1.68 1.05 1.16 1.05 0.82 1.05 0.93 1.07 1.26 1.1 1.18 1.19 0.81 1.19 0.81 1.2 1.28 1.23 1.18 1.23 0.71 1.24 Note: This problem has a reduced data set for ease of performing the calculations required. This differs from the data set given for this problem in the text. Compute the least-squares line for predicting the long-term measurement from the short-term measurement.…arrow_forwardInterpret the following results in a correlation analysis:a. r = 0.27, n =100b. r=0.27,n=16c. r=-0.75,n=16d. r = 0.02, n =100arrow_forward1. The observed and model simulated average daily flow in month flow at the outlet of a river catchment during a given period is presented as follows. Predicted flow Observed flow 0.25 0.30 0.70 0.73 0.80 0.87 0.71 0.90 0.71 0.65 1.60 1.45 0.90 0.70 0.71 0.61 0.24 0.22 1.00 0.64 0.81 1.00 1.05 0.90 0.46 0.48 0.27 0.23 0.80 0.24 0.32 0.42 0.80 0.89 (i) Evaluate the model performance based on any two computed statistical measures of performance of your choice. (ii) Explain possible reasons for model performance observed in (i) above. (Hint: Refer to reading material provided on model evaluation by Moriasi et al., 2007)arrow_forward
- 4. It is determined that an experimental data taken for T as a function of time, is a first order system, following the trend line of y = yoe. The data taken for various times is shown in table below. Approximate the time constant for this experiment. Show your work. T 0.00 0.50 3.00 5.00 5.50 6.00 6.50 7.00 7.50 11.00 14.00 17.00 22.00 25.00 Y 23.00 22.43 20.13 18.81 18.54 18.29 18.05 17.84 17.63 16.57 16.01 15.64 15.31 15.20arrow_forwardWLEY 6-44. The data that follow are DC output from a windmill (y) and wind velocity (x). (a) Draw a scatter diagram of these data. What type of rela- tionship seems appropriate in relating y to x? (b) Fit a simple linear regression model to these data. (c) Test for significance of regression using a = 0.05. What conclusions can you draw? (d) Plot the residuals from the simple linear regression model versus y, and versus wind velocity x. What do you con- clude about model adequacy? (e) Based on the analysis, propose another model relating y to.x. Justify why this model seems reasonable. (f) Fit the regression model you have proposed in part (e). Test for significance of regression (use a = 0.05), and graphically analyze the residuals from this model. What can you conclude about model adequacy? Observation Number 1 NM & in eor 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Wind Velocity (MPH), x 5.00 6.00 3.40 2.70 10.00 9.70 9.55 3.05 8.15 6.20 2.90 6.35 4.60 5.80 7.40…arrow_forward4. Develop a model using regression analysis for trip production using the following data. Zone Number Trip production Trip Vehicle Employment attraction ownership 1 200 1 1000 256 1.5 1250 345 2500 6. 451 2.8 3600 5 6.5 555 4200 6. 7 600 4 4500 3. 2. 3. 2. 3. 4.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Elements Of ElectromagneticsMechanical EngineeringISBN:9780190698614Author:Sadiku, Matthew N. O.Publisher:Oxford University PressMechanics of Materials (10th Edition)Mechanical EngineeringISBN:9780134319650Author:Russell C. HibbelerPublisher:PEARSONThermodynamics: An Engineering ApproachMechanical EngineeringISBN:9781259822674Author:Yunus A. Cengel Dr., Michael A. BolesPublisher:McGraw-Hill Education
- Control Systems EngineeringMechanical EngineeringISBN:9781118170519Author:Norman S. NisePublisher:WILEYMechanics of Materials (MindTap Course List)Mechanical EngineeringISBN:9781337093347Author:Barry J. Goodno, James M. GerePublisher:Cengage LearningEngineering Mechanics: StaticsMechanical EngineeringISBN:9781118807330Author:James L. Meriam, L. G. Kraige, J. N. BoltonPublisher:WILEY
![Text book image](https://www.bartleby.com/isbn_cover_images/9780190698614/9780190698614_smallCoverImage.gif)
Elements Of Electromagnetics
Mechanical Engineering
ISBN:9780190698614
Author:Sadiku, Matthew N. O.
Publisher:Oxford University Press
![Text book image](https://www.bartleby.com/isbn_cover_images/9780134319650/9780134319650_smallCoverImage.gif)
Mechanics of Materials (10th Edition)
Mechanical Engineering
ISBN:9780134319650
Author:Russell C. Hibbeler
Publisher:PEARSON
![Text book image](https://www.bartleby.com/isbn_cover_images/9781259822674/9781259822674_smallCoverImage.gif)
Thermodynamics: An Engineering Approach
Mechanical Engineering
ISBN:9781259822674
Author:Yunus A. Cengel Dr., Michael A. Boles
Publisher:McGraw-Hill Education
![Text book image](https://www.bartleby.com/isbn_cover_images/9781118170519/9781118170519_smallCoverImage.gif)
Control Systems Engineering
Mechanical Engineering
ISBN:9781118170519
Author:Norman S. Nise
Publisher:WILEY
![Text book image](https://www.bartleby.com/isbn_cover_images/9781337093347/9781337093347_smallCoverImage.gif)
Mechanics of Materials (MindTap Course List)
Mechanical Engineering
ISBN:9781337093347
Author:Barry J. Goodno, James M. Gere
Publisher:Cengage Learning
![Text book image](https://www.bartleby.com/isbn_cover_images/9781118807330/9781118807330_smallCoverImage.gif)
Engineering Mechanics: Statics
Mechanical Engineering
ISBN:9781118807330
Author:James L. Meriam, L. G. Kraige, J. N. Bolton
Publisher:WILEY
Interpolation | Lecture 43 | Numerical Methods for Engineers; Author: Jffrey Chasnov;https://www.youtube.com/watch?v=RpxoN9-i7Jc;License: Standard YouTube License, CC-BY