Engr 1020 Freshman Engineering Seminar Final Assessment Name

Engr 1020 Freshman Engineering Seminar Finalassessmentnamedatedirecti

SHOW YOUR COMPLETE WORK (steps, calculations, assumptions, etc.) if you would like to RECEIVE ANY CREDIT NOTE 1: This is an Individual Assessment and NOT a Group Assessment. If any solutions are the same, then each of those students will receive a grade of a “0” on the Final Assessment and those students will repeat the course again next semester. NOTE 2: For each problem, you can either solve the problem using R or MATLAB®/GNU Octave (no Microsoft Excel) and/or you can solve the problem by hand on engineering paper and/or here (feel free to use the backside). If using R or MATLAB®, then include your complete source code (input) along with your answers (output).

Be sure to include units and use significant figures appropriately. Write neatly in pencil — work in pen will NOT be accepted. You will have until 4:55 PM on Wednesday, 2 December 2015 and no LATER to turn the Final Assessment in to me in Holland Hall 106, thus the Assessment can not be e-mailed. Cite your references as needed (use the citations at the end of this Assessment and/or the Mid-Term Report for reference). Read the directions carefully. Total possible points (including Extra Credit): 175 points.

Paper For Above instruction

This assessment covers a wide range of engineering concepts, ethics, problem-solving skills, programming proficiency, and data analysis. Students are tasked with demonstrating comprehensive understanding through calculations, coding, written explanations, and data interpretation. Emphasis is placed on showing complete work, detailed assumptions, proper units, and significance in results. The assessment integrates theoretical knowledge with practical application, requiring students to utilize software tools such as R or MATLAB® for problem-solving, and to articulate their reasoning clearly. Ethical questions challenge students to consider the implications of engineering practices on society and the environment. Data analysis problems assess proficiency in statistical measures and data interpretation. Programming tasks involve generating tables and performing financial calculations, emphasizing accuracy in currency conversions and interest computations. Overall, the assessment aims to evaluate the student’s ability to combine analytical skills with ethical considerations in engineering. It is crucial that all solutions reflect a thorough process, including steps, assumptions, calculations, and correct referencing, to meet the standards of rigorous engineering practice.

Answer

Introduction

The comprehensive nature of this assessment aims to evaluate various fundamental aspects of engineering education, including technical problem-solving, ethical considerations, data analysis, programming skills, and communication. The integration of these elements reflects the multifaceted role of an engineer, combining technical proficiency with ethical responsibility and effective communication. This paper addresses each component of the assessment in turn, providing detailed solutions, explanations, and critical insights into each topic.

Engineering Ethics and Professional Practice

Students are first asked to identify six undergraduate degree programs offered by the Texas State University (TSU) College of Engineering. Examples include Mechanical Engineering, Electrical Engineering, Civil Engineering, Computer Engineering, Environmental Engineering, and Software Engineering. Furthermore, understanding the scope of the engineering code of ethics is essential; it applies primarily to licensed professional engineers and those directly associated with engineering practice, including graduates who actively hold engineering licenses. Land surveyors, however, are often governed by separate professional codes.

Ethically, the practice of engineering involves safeguarding the environment, human health, and societal prosperity. The code of ethics underscores responsibilities toward protecting ecosystems and ensuring public safety. When faced with tradeoffs such as risk vs. benefit or safety vs. economy, engineers must exercise judgment beyond mere adherence to the ethical code, considering broader impacts and stakeholder interests.

The Licensing Examination for senior undergraduates aiming for professional registration is called the Principles and Practice of Engineering (PE) exam. Upon passing, candidates receive the PE license, which authorizes them to practice independently and sign engineering documents legally. To sit for this exam, candidates must have completed their undergraduate coursework and accumulated requisite work experience, typically at least four years under the supervision of a licensed engineer.

Problem Solving and Programming

Regarding programming in R, the commands provided illustrate sequence generation and data structure manipulation. For example, the command 'single

One data set related to radioactive isotopes such as Beryllium-7, Lead-212, and Thallium-208 is analyzed through statistical measures. For each isotope, measures of central tendency—mean, median, and mode—are calculated to understand typical activity levels. Measures of dispersion—variance, standard deviation, and range—assess variability within the data, which is essential for quality control and research reliability.

Material Lifecycle and Environmental Considerations

Engineers should prioritize the entire lifecycle of their designs, considering environmental impacts from production to disposal. The excerpt emphasizing recycling illustrates that superficial environmental approaches can be inadequate or counterproductive. Ethical engineering requires a thorough understanding of material sustainability and ecological effects, advocating for a cradle-to-grave analysis.

I agree with the excerpt from 'Cradle to Cradle' that simply recycling a material does not automatically render it eco-friendly; intentional design for recyclability is key. Engineers have a responsibility to innovate with environmental integrity in mind, ensuring that materials and processes minimize ecological harm across their entire lifecycle.

Data Analysis and Statistical Measures

Using the provided datasets for different isotopes, statistical measures reflect the central tendency and dispersion, highlighting the consistency and variability of radioactivity levels. For example, calculations of mean and standard deviation reveal the average activity and spread, guiding safety protocols or scientific interpretations.

Linear Regression and Interpolation

Given data on the tensile strength of a plastic over time, fitting a straight line involves using least squares regression to model the relationship. The equation derived allows estimating tensile strength at 63.5 minutes. For example, if the regression yields: Tensile Strength = m × time + b, substituting 63.5 yields the predicted value.

Linear interpolation uses the two data points surrounding 63.5 minutes to interpolate the tensile strength. Assuming data at t1 and t2, and their corresponding strengths s1 and s2, the interpolated value is:

value = s1 + (s2 - s1) * (63.5 - t1) / (t2 - t1)

This provides an approximate but efficient estimate.

The relative error compares the regression-based estimate to the interpolation, calculated as:

Relative Error = |(Estimate - Actual) / Actual| × 100%

A low relative error indicates model accuracy.

Risk and Uncertainty Analysis

Analysis of launch data involves calculating the average error, which can be misleading as it does not account for error magnitude direction or variability. Root mean square error (RMSE) provides a better indicator of accuracy by emphasizing larger errors. Standard deviation further quantifies the spread of errors, informing reliability and consistency measures.

Probability and Statistical Applications

Calculating probabilities, such as two workers both opposing safety regulations, involves hypergeometric distributions due to dependent selection without replacement. Combinations are used to determine total possible teams or arrangements, based on binomial coefficients.

Failure Rate and Ethical Considerations

Failure rate is derived by dividing the total failures by operation hours: 8,524 failures / 27,160 hours ≈ 0.313 failures/hour. If the maximum acceptable failure rate is 0.293, then the system exceeds this threshold, indicating unacceptable performance. Ethical engineering practice mandates reporting accurate data; altering failure data contradicts professional integrity and could jeopardize safety and compliance.

Financial Calculations and Currency Conversion

Future value calculations use compound interest formulas to project investments. Given the principal (£285,940.45), interest rate (7.1284%), and period (17 years), the future worth in US dollars is obtained via:

F = P × (1 + i)^n × exchange rate

This enables assessing foreign investments. Similarly, loan payments are computed using amortization formulas, translating interest rates into annual payments. Currency conversion tables facilitate understanding of exchange rates and aid in international financial planning.

Interest Rates and Inflation

Effective annual inflation rate with 20% monthly inflation is calculated as:

(1 + 0.20)^12 - 1

which results in a significantly high rate. For interest rates compounded quarterly, the effective annual rate is:

 (1 + nominal rate / 4)^4 - 1

These calculations are vital for financial risk assessment and planning.

Conclusion

This assessment encapsulates critical engineering disciplines, emphasizing the importance of thorough problem solving, ethical considerations, data analysis, and effective communication. Engineers must balance technical precision with societal responsibility, integrating analytical tools, programming skills, and ethical judgment to address complex challenges. The exercises demonstrate that successful engineering practice hinges on meticulous work, integrity, and a holistic view of environmental and societal impacts.

References

• Brockman, J. B. (2009). Introduction to Engineering: Modeling and Problem Solving.
• Carmichael, D. G. (2013). Problem Solving for Engineers.
• Chapra, S. C. (2008). Applied Numerical Methods with MATLAB for Engineers and Scientists.
• Etter, D. M. (1996). Introduction to MATLAB For Engineers and Scientists.
• McDonough, W., & Braungart, M. (2002). Cradle to Cradle: Remaking the Way We Make Things.
• Miller, I., Freund, J. E., & Johnson, R. A. (1990). Probability and Statistics for Engineers.
• National Council of Examiners for Engineering and Surveying (NCEES). (2011). Fundamentals of Engineering (FE) Handbook.
• Olia, M., P.E., & Contributing Authors. (2015). Barron’s FE (Fundamentals of Engineering Exam).
• U.S. Environmental Protection Agency (EPA). (2011). EPA RadNet Radiation Data.
• Tennessee Board of Architectural and Engineering Examiners. (2013). Engineer Information & Guidelines.