Abhijith SivaprasadanM.Sc. Sustainable Energy Engineering · KTH · Stockholm, Sweden
General / Portfolio
I connect thermal-fluid engineering, energy-system modelling and research software. My background spans a Siemens Energy CFD/CHT thesis, Kerala2040 power-system resilience research, dynamic thermal-storage modelling, industrial energy methodology at Alleima and professional backend development at QBurst. I can move between component physics, system-level assumptions and inspectable software outputs, and make clear which questions each model can answer.
01 / Selected work
A focused selection. Open a case study for methods, results and limitations, or follow the skill dossiers below for the complete related record.
Public-data research freeze (23 October 2026) on Kerala's electricity-system stress, with observed SLDC daily targets, ERA5 retrospective demand analysis, hydro timing and bounded transmission screening. Not a validated planning model.
Python · PyPSA · OSeMOSYS · ERA5 · HiGHS · GIS · pytest
Industrial thesis at Siemens Energy Finspång combining preliminary NI-DAQ/LabVIEW commissioning and supervised heater-failure troubleshooting with a 15-run numerical CFD/CHT comparison of Pulsatorn reducer geometries.
ANSYS Fluent · CFD/CHT · k-omega SST · NI-DAQ · LabVIEW · Siemens NX
Techno-economic screening of industrial thermal energy storage with state-of-charge-dependent discharge constraints derived from dynamic models. Packed-bed, molten-salt and PCM cases are compared with explicit verification, sensitivity and validation boundaries.
Python · Pyomo · HiGHS · Modelica · FMI/FMPy · SALib
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.
Python · Modelica · Pyomo · HiGHS · FMI/FMPy · Streamlit · pytest
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.
Python · Pyomo · HiGHS · Streamlit · NumPy · pytest
Modern Fortran educational gas-turbine and CCGT simulator. The v2.0.0-beta.1 source-only prerelease is archived on Zenodo (10.5281/zenodo.23679426); release CI passed, while GUI and industrial asset validation remain unaccepted.
Fortran 2008 · Python · Win32/GDI+
Industrial energy performance methodology covering KPI/EnPI design, metering readiness, load-driver logic, deviation detection and regulatory comparison for decarbonization decisions.
Python · ISO 50001 · EU EED · Excel
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.
Python · Streamlit · Excel · PDF reporting
02 / Experience
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, commissioned the measurement chain for a planned validation campaign 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.
ANSYS Fluent · NI-DAQ · LabVIEW · Siemens NX · Teamcenter PLM2020 · Conjugate Heat Transfer · Compressible CFD · Root Cause Analysis
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
Approximately 21 months of professional backend engineering, starting with Go and later moving into JavaScript/TypeScript and NestJS. Worked on production APIs, reliability fixes and automated tests including negative-path validation, using Git, Docker and Postman in collaborative teams. Formal employment title: Engineer.
Go · JavaScript · Git · Docker · TypeScript · NestJS · PostgreSQL · Postman · REST APIs · Agile Development
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.
03 / Skills & evidence
Each skill opens its own page with all related public projects, roles, coursework, training and supporting material.
04 / Education
Completed the M.Sc. programme, including the 30 ECTS thesis within the 120 ECTS total; degree certificate in process. Specialisation: Energy Supply through Clean Conversion Technologies. Grade A in Numerical Heat Transfer and AI Applications. The record also includes a 3 ECTS Aalto/Unite! elective.
Mechanical engineering foundation with coursework, design competitions and the final-year interactive robot project.
Credited exchange elective covering lifecycle and circular-economy perspectives on energy storage; not a separate degree.
05 / Supporting material
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.
Let’s connect
For cross-disciplinary engineering and general applications.
abhijithsivaprasadan@gmail.com