Challenge 5: Climate Change and Use of Natural Resources and Raw Materials

Weather forecasting is based on mathematical models capable of predicting devastating natural disasters such as hurricanes, floods or forest fires. The consequences of natural phenomena such as tsunamis, snow and rock avalanches or cold snaps can often be mitigated using MSO-ED tools. In addition, the evolution of climate change and global warming is currently carried out based on mathematical simulations, which helps to assess the magnitude of what is already the first global challenge.

The greatest challenge of the coming decades will be to defend the environment through achieving sustainable economic development. This is a field, halfway between challenges 3 and 5, and where MSO-ED tools can make enormous contributions. For example, energy management can be facilitated by intelligent decision systems based on properly developed mathematical algorithms. The same can be done for urban waste collection operations, or fleet management for delivery in the city. Building management is another field of application of the MSO-ED tools; An appropriate algorithm can calculate the air quality requirements and thermal conditions of each room in a building, ensuring the minimum welfare conditions required by law, while minimizing energy use. We will also mention simulation tools to help prototype new cars (minimizing the burning of polluting fuels) or electric motors.

On the other hand, the challenges faced by companies within Industry 4.0 and 5.0 show an unprecedented level of complexity, requiring holistic approaches and solution processes based on optimized algorithms. Decision makers need advanced tools that enable long-term risk analysis, clean processes, and prototype improvements, along with an appropriate set of optimization and control methods. The key technologies of these processes are usually very complex and require the support of highly qualified experts, which are often not available in Spanish SMEs (particularly innovative technology-based companies and start-ups), which affects to the economic and financial results of the companies. In addition, the providers of the necessary skills are spread over different areas of specialization in universities, research and technological institutions. These characteristics require the collaboration and integration of different advanced providers and other innovation players in different sectors and regions. This integrative role is one of the proposed goals for the PET MSO-ED platform.

• Capacities of MSO-ED Technologies in the field of Challenge 5
  • Simulation, prediction and control of polluting emissions.
  • Simulation and optimization of production and distribution processes.
  • Comprehensive optimization of product and goods supply chains, made up of raw material suppliers, production plants, assembly plants, product sales and recycling centers from customers to control plants, and from there to production plants and assembly (closed-up supply chain management).
  • Modeling and simulation of forest fires. Help algorithms for prevention, control and extinction. Optimization of the planning of the use of land and air resources for their extinction.
  • Simulation, prediction and impact of natural disasters such as floods and earthquakes. Optimization of the mitigation of its effects before the event.
  • Optimization of emergency action, through the location of shelters and deposits, collection of resources, and distribution of essential material.
  • Simulation and prediction of water quality. Optimization of the sustainable planning of the exploitation of hydrographic basins for industrial, energy generation, agricultural and domestic purposes.
  • Optimization of the planning of sustainable forest exploitation.
  • Optimization of irrigation planning for agricultural and livestock purposes.

• Success stories already implemented in the field of Challenge 5
  • Predict the effects of a tsunami. See math-in Success Case Book, pg. 7.
  • Predictive tool for pollution episodes and pollution events in a thermal plant. See math-in Success Case Book, pg. 6.
  • Flow simulation in rivers and estuaries. See math-in Success Case Book, pg. 9.
  • Irrigation, humidity and temperature control tool in greenhouses. See math-in Success Case Book, pg. 37.
  • Diachronic assessment of the use of sewage sludge in agriculture: production, biodiversity, phosphorus and heavy metals.
    Forest fire prediction. See math-in Success Case Book, pg. 10.
  • Critical emergency missions with manned and unmanned aerial vehicles in cooperative flights. Math-in success case published in the database of the European network EU-Maths-IN.
  • Simulation and optimization of new processes and alloys of microalloyed steels for hot forging of automotive crankshafts. See math-in Success Case Book, pg. 5.
  • Assists in the design of energy supply systems for ships in ports. Math-in success case published in the database of the European network EU-Maths-IN.
  • Predictive maintenance of air conditioning systems. Math-in success stories published in the EU-Maths-IN European network database and available at link1 and link2.
  • Metal casting processes and metallurgical treatment. Math-in success case published in the database of the European network EU-MATHS-IN.
    Mathematical modeling and numerical simulation in order to improve the efficiency and productivity of industrial furnaces for metal purification. See math-in Success Case Book, pg. 3. 4.
  • Resolve depth in satellite images. See math-in Success Case Book, pg. 19.
  • Lubricate ship propellers with sea water. See math-in Success Case Book, pg. 31.
  • Mathematical modeling and numerical simulation in order to improve the efficiency and productivity of industrial furnaces for metal purification. See math-in Success Case Book, pg. 3. 4.