Rail Noise-Vibration PhD Thesis
Budget: ₹12,500 – ₹37,500 INR
I am finalising a PhD in Civil Engineering that investigates noise and vibration in railways, with the spotlight on the precise measurement and statistical analysis of both phenomena. My research questions are framed, the experimental layout is approved, and I have already gathered a preliminary set of field recordings. What I need now is expert support to convert this material into a cohesive, publication-ready dissertation.
Scope of work
• Refine and expand the literature review so it accurately positions my study within current railway acoustics and ground-borne vibration research.
• Validate my measurement methodology (instrument selection, sensor placement, calibration procedures) and present it in a clear, reproducible format.
• Perform advanced signal processing and statistical analysis on the datasets I provide—Fourier transforms, octave-band breakdowns, vibration dose value calculations, and regression or machine-learning correlations between operational parameters and measured levels. I usually work in MATLAB and Python; feel free to suggest equivalent or better tools if you have a strong rationale.
• Draft or polish result chapters, discussion, and conclusions, ensuring every claim is backed by data and referenced to relevant standards (e.g., ISO 3095, ISO 2631) or peer-reviewed studies.
• Edit the entire thesis to meet university formatting guidelines (Chicago author-date citations, 12 pt Times, 1.5-line spacing) and deliver a document that will pass both similarity checks and the scrutiny of a civil-engineering examination panel.
Acceptance criteria
1. All figures, tables, and appendices are numbered, captioned, and cross-referenced correctly.
2. Statistical outputs are reproducible from supplied code/notebooks.
3. Plagiarism report below 10 %.
4. Final thesis submitted in both Word and PDF, ready for printing and electronic submission.
If you have previously published or supervised work on rail or transport acoustics, vibration modelling, or structural-borne noise, your experience will be invaluable. Let me know how you would tackle the signal processing and data interpretation, the approximate timeline, and any milestones you recommend.
Scope of work
• Refine and expand the literature review so it accurately positions my study within current railway acoustics and ground-borne vibration research.
• Validate my measurement methodology (instrument selection, sensor placement, calibration procedures) and present it in a clear, reproducible format.
• Perform advanced signal processing and statistical analysis on the datasets I provide—Fourier transforms, octave-band breakdowns, vibration dose value calculations, and regression or machine-learning correlations between operational parameters and measured levels. I usually work in MATLAB and Python; feel free to suggest equivalent or better tools if you have a strong rationale.
• Draft or polish result chapters, discussion, and conclusions, ensuring every claim is backed by data and referenced to relevant standards (e.g., ISO 3095, ISO 2631) or peer-reviewed studies.
• Edit the entire thesis to meet university formatting guidelines (Chicago author-date citations, 12 pt Times, 1.5-line spacing) and deliver a document that will pass both similarity checks and the scrutiny of a civil-engineering examination panel.
Acceptance criteria
1. All figures, tables, and appendices are numbered, captioned, and cross-referenced correctly.
2. Statistical outputs are reproducible from supplied code/notebooks.
3. Plagiarism report below 10 %.
4. Final thesis submitted in both Word and PDF, ready for printing and electronic submission.
If you have previously published or supervised work on rail or transport acoustics, vibration modelling, or structural-borne noise, your experience will be invaluable. Let me know how you would tackle the signal processing and data interpretation, the approximate timeline, and any milestones you recommend.
Related categories:
Python
Matlab and Mathematica
Civil Engineering
Statistical Analysis
SPSS Statistics
Signal Processing
MATLAB