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GP-CH-0B962LUChemicalOpen for request

Agro-waste valorisation decision system

A decision-support system for comparing agro-waste conversion pathways using feedstock properties, process yields, mass and energy balances, economics, and environmental indicators.

  • Nuxt
  • Vue
  • FastAPI
  • PostgreSQL
  • Python
  • Pandas
  • Pyomo
  • Docker

Project definition

Problem statement

Rice straw, bagasse, husk, shells, and other agro-residues differ in moisture, ash, composition, seasonality, collection radius, competing uses, and suitability for conversion pathways.

The engineering problem is to reject technically incompatible options, calculate comparable material and energy outputs, and rank feasible pathways without hiding uncertain data or subjective decision weights.

Project objectives

  • Represent selected Indian agro-waste feedstocks, composition, quantity, seasonality, location, and competing uses.
  • Model documented conversion pathways such as briquetting, anaerobic digestion, biochar, or selected biochemical products.
  • Perform mass and energy balances and screen moisture, ash, scale, logistics, and product constraints.
  • Compare capital, operating, logistics, product, energy, emissions-proxy, and residue indicators.
  • Rank options through transparent multi-criteria methods and sensitivity analysis.

System design

System modules

01

Feedstock registry

Stores source, quantity, moisture, ash, composition, seasonality, current use, location, and data confidence.

02

Pathway library

Defines process steps, accepted feed ranges, yields, utilities, products, residues, and evidence source.

03

Balance and screening engine

Calculates material and energy flows and flags incompatible or missing assumptions.

04

Economic and environmental model

Estimates collection, transport, preprocessing, conversion, product value, energy, and selected environmental indicators.

05

Decision dashboard

Shows feasible pathways, flows, costs, indicators, ranks, uncertainty, and weight sensitivity.

Methodology

System workflow

  1. 01
    Define feedstock case

    The student selects a prepared residue, quantity, composition, collection area, seasonality, and present use.

  2. 02
    Screen pathways

    The engine checks feed and scale requirements and records exclusions with reasons.

  3. 03
    Calculate cases

    Mass, energy, logistics, economic, and environmental indicators are calculated for feasible options.

  4. 04
    Rank options

    Normalised criteria and declared weights produce a transparent decision matrix.

  5. 05
    Test sensitivity

    Yield, moisture, distance, price, scale, and decision weights are varied to identify robust choices.

Demonstration scenario

A prepared rice-straw case is screened for briquetting, anaerobic digestion, and biochar. Moisture and ash assumptions affect the feasible routes. The dashboard compares products, energy, logistics, cost, and environmental indicators, then shows whether the ranking changes when collection distance and decision weights vary.

Engineering

Technical architecture

Web application
Nuxt and Vue for feedstock setup, pathway flows, criteria tables, ranking, and sensitivity charts.
Decision API
FastAPI for feedstocks, pathways, balances, scenarios, rankings, and exports.
Data layer
PostgreSQL for feedstock records, process parameters, sources, scenarios, balances, costs, and scores.
Engineering engine
Python and Pandas for units, mass and energy balances, logistics, economics, normalisation, and uncertainty.
Optimisation layer
Pyomo or deterministic search for selected allocation cases with feedstock, capacity, and demand constraints.

Testing

Evaluation

Evaluation measures

  • Mass and energy balance closure for prepared pathway cases
  • Correct rejection of incompatible feedstock and process combinations
  • Agreement with manually calculated product, utility, and cost examples
  • Ranking correctness under prepared decision matrices
  • Rank stability under parameter and decision-weight sensitivity
  • Calculation and dashboard response time across feedstocks, pathways, and scenarios

System boundaries

  • The selector provides pre-feasibility comparisons based on documented secondary or prepared data.
  • It does not replace laboratory characterisation, pilot trials, detailed process design, market study, or environmental approval.
  • Availability excludes residues required for soil health, fodder, fuel, or other documented competing uses.
  • Thermal, biological, chemical, pressure, and emissions hazards require specialist design and regulatory review.

Included

  1. 01Feedstock, pathway, location, and criteria interface
  2. 02Mass-balance, screening, economics, and ranking modules
  3. 03Product, energy, cost, environment, and sensitivity dashboards
  4. 04Prepared Indian agro-waste cases, pathway data, and results
  5. 05Complete source code in a private GitHub repository
  6. 06Complete project documentation with synopsis, abstract, methodology, process-flow diagrams, decision results, screenshots, and conclusion
  7. 07Setup and usage guide

Project record

No buyer information is collected on this page.

Permanent project ID
GP-CH-0B962LU
Catalogued
21 Aug 2026
Completed
Pending
Verified
Pending
Demonstration
Added when ready

Handover

After purchase

  1. 01
    Payment is confirmed

    The project is marked unavailable and cannot be purchased again.

  2. 02
    Repository access is granted

    The buyer's submitted GitHub account receives access to the private repository.

  3. 03
    The purchase record is delivered

    The certification sheet is prepared from the reviewed buyer details and sent privately by email.