Model-assisted scale-up and R&D engineering support

Chemical · Energy · Manufacturing

Process plant

About

ONB Engineering is a specialty R&D and consulting firm working across chemical, energy, and manufacturing systems. We build decision-grade models-flowsheets, kinetics, reduced-order tools, and CFD when warranted-and translate them into clear, usable outputs: operating windows, scale drivers, cost and carbon tradeoffs, and the shortest test plan that reduces uncertainty. We keep assumptions explicit and traceable, so the work can move from analysis to execution without friction.

20+ R&D projects completed for global clients, including startups, universities, government agencies, investors, and industry.

For Industrial & Startup Teams

Engineering support for technology development, scale-up, optimization, and decision-making.

  • Process development, modeling & optimization (from unit models to full flowsheets)
  • Technology and product scaling: pilot planning, sizing logic, and operating windows
  • Techno-economic analysis and decision packages for internal gates, partners, and investors
  • Life-cycle assessment and carbon strategy inputs (when the decision requires it)
  • Energy efficiency and cost-reduction strategies for industrial operations and retrofits
  • Advanced control, data-driven optimization, and predictive maintenance concepts (project-dependent)

Domain experience spans gasification, pyrolysis, Fischer–Tropsch, hydrogen generation, CCUS/CCU, catalysis/reaction engineering, specialty chemicals, advanced manufacturing, circular economy processes, and energy storage materials.

For R&D Partners

A technical partner for universities, labs, and proposal teaming-structured work, clean interfaces, clear outputs.

  • Work packages: process modeling, CFD/CPFD studies, TEA/LCA, analysis, and reporting
  • Proposal support: scope definition, deliverables, schedules, and technical narrative
  • Reproducible workflows and assumption traceability (NDA/IP-aware)
  • Training and knowledge transfer to make partners self-sufficient post-engagement

Mini Case Studies

Selected examples (anonymized where appropriate). Many projects are under NDA.

Case Study 01

Plasma gasifier optimization (15 ton/day)

Thermochemical conversion · multi-scale modeling for scale-up decisions

  • Objective: improve thermal stability and yield while reducing plasma demand and operational risk.
  • Model(s): multi-scale CFD + reduced-order Python model to map reactor performance across scenarios.
  • Validation: closure checks + reconciliation to baseline operating behavior; sensitivity ranking on dominant drivers.
  • Deliverables: scenario library, operating window, and recommendation memo for implementation.
  • Outcome: plasma demand −12%, Tmax reduced by 120 °C, syngas yield +15%, slag-flow window stabilized (risk index 0.36 → 0.71).

Case Study 02

Graphite pilot scale-up (86 ton/yr): heat integration + sizing sweep

Electrochemical manufacturing · pilot design basis and scale drivers

  • Objective: identify the operating window for purity while minimizing power and CAPEX.
  • Model(s): custom flowsheet for electrolyzer, solids handling, and multiphase units; integrated sizing sweep.
  • Validation: consistency checks and parameter sweeps against constraints and pilot design logic.
  • Deliverables: optimized process basis, sizing outcomes, and clear tradeoffs for design selection.
  • Outcome: power −31%, CAPEX −22%, optimum window for spec purity identified (risk 0.43 → 0.82).

Case Study 03

Ethanol upgrading to ethyl acetate + acetic acid (2,000 & 50,000 tpa)

Aspen Plus process assessment · separation strategy · TEA + LCA

  • Objective: develop a decision-ready process assessment at two scales and define the separation train strategy.
  • Model(s): Aspen Plus v12 flowsheet (NRTL), reactor representation with conversion/selectivity, equipment sizing, heat integration.
  • Validation: thermodynamic sanity checks, internal consistency, and bounded ranges on key assumptions.
  • Deliverables: flowsheet + H&MB, equipment list/sizing, capex/opex, TEA, and LCA.
  • Outcome: clear scale comparison, dominant cost/carbon drivers, and separation approach aligned to product specs (99.5 wt.% targets).

Case Study 04

Integrated model suite: Aspen + Python + electrolysis growth model + TEA/LCA

Process model development · robust scenario sweeps · scale from pilot to 300+ tpa

  • Objective: build a stable modeling backbone for scale-up decisions, hardware sizing, and scenario evaluation.
  • Model(s): Aspen Plus process model + Python sequential flowsheet; electrolysis cell & growth model; TEA and LCA calculators.
  • Validation: mass/energy closure + reconciliation to available time-trial data; sensitivity ranking for decision levers.
  • Deliverables: unit models, scenario library, and decision memo translating model outputs into pilot requirements.
  • Outcome: converged, sweep-ready model inventory that made operating windows and scaling drivers explicit.

Case Study 05

LCA calculator for methanol (PCF + impact categories) with validation cases

Scenario-ready sustainability tooling for non-specialists and experts

  • Objective: enable fast, consistent product carbon footprint and impact evaluation across boundaries (G2G / C2G / CtG).
  • Model(s): Excel-based LCA calculator with scenario library, export formats, and structured reporting.
  • Validation: benchmark scenarios and built-in sanity checks to catch inconsistent inputs.
  • Deliverables: calculator + user manual + reporting outputs (scope breakdown and impact categories).
  • Outcome: repeatable LCA workflow that supports scenario comparison and decision discussions.