Abhijith SivaprasadanM.Sc. candidate at KTH · Stockholm, Sweden
General / Portfolio
Engineering, connected.
I connect mechanical engineering, energy-system modelling and software development. My background spans thermal-fluid research at Siemens Energy, industrial energy methodology at Alleima and backend development at QBurst.
An open-source two-boiler steam-and-power twin with a carbon-aware Pyomo/HiGHS scheduler, OpenModelica FMI 2.0 simulation and a local Streamlit advisory GUI. Synthetic and uncalibrated; not an ABB product or live control system.
Seven months embedded at Siemens Energy Finspång conducting compressible CFD/CHT, high-temperature instrumentation and root-cause analysis for the Pulsatorn dynamic pressure sensor calibration rig.
Local electricity-investment GUI and shared Pyomo/HiGHS planner, with audited market coverage and 175 extracted public input references. Synthetic and uncalibrated; normalization, price-target decisions and weather conversion still gate historical fitting.
How do degradation and thermal transients affect a gas turbine? A Make-built educational simulator checked against hand calculations, an analytical transient and repeatable sensor-noise tests. Not commercial-engine validation.
How does energy use change with production? Baseline normalisation and residual diagnostics checked against known-linear data, with explicit missing-meter handling. Alerts are not root-cause diagnoses.
Final-year interactive robot project combining IRJET control-system/subsystem integration work with the published frame and locomotion design: Raspberry Pi/cloud control, surveillance, SOC indication, steering integration, drivetrain sizing and ANSYS deformation screening.
Raspberry Pi · CAD · ANSYS · BLDC motor controller · Servo control · IRJET manuscript
Seven months embedded at Siemens Energy Finspang in the Fluid Dynamic Lab. Conducted numerical investigation of steady-state thermo-fluid performance of a reducer geometry for a high-temperature dynamic pressure sensor calibration rig (Pulsatorn). Built compressible CFD and conjugate heat transfer models in ANSYS Fluent (k-omega SST), conducted three-level mesh independence study, and applied Biot number analysis to decompose thermal performance. Identified flow-regime asymmetry between geometry variants (Ma 0.990 near-choked vs Ma 1.006 supersonic vena contracta). Also commissioned NI-DAQ measurement chains, modified LabVIEW VIs, ran independent test campaigns at up to 700 C, and conducted a formal root cause analysis of a heater failure resulting in an approved project scope revision. Used Siemens NX and Teamcenter PLM2020 throughout. Supervisor: Prof. Jens Fridh, KTH. Thesis: TRITA-ITM-EX 2026:14.
Developed and independently validated a quantitative methodology for industrial energy performance mapping, covering KPI/EnPI design, load-driver logic, metering-gap assessment, deviation detection from noisy operational data and regulatory comparison. The work was desk-based method development and decision-support framing rather than hands-on plant execution, with electrical utilities and compressed air treated as relevant electrification pathways. Proprietary site detail is not republished.
Python · ISO 50001 · EU EED · KPI/EnPI Design · Energy Performance Mapping · Industrial Energy Analysis · Structured Reporting
Implemented and maintained backend API endpoints in TypeScript/NestJS, delivered reliability fixes, wrote endpoint tests including negative-path validation and used Postman automation in production-oriented agile teams.
Contributed to KTH plastic pyrolysis research by reviewing reactor concepts and cost-analysis drivers for oil extraction from polymer waste, supporting early-stage technical and economic feasibility evaluation.
This is a cross-disciplinary selection, not a claim of equal depth in every area. Professional roles, academic projects and independent tools are labelled separately. The thesis had experimental limitations; industrial work does not establish plant savings, and exploratory models are not validated system forecasts.
Source case studies remain authoritative. Private inputs and restricted project details are not published.
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For cross-disciplinary engineering and general applications.