Interactive Environmental Engineering
Environmental Systems - Complex and Uncertain
The environment is one of the most challenging and important systems to simulate. In future, our society needs to better predict and then minimize its environmental impact. Environmental systems are a complex and dynamic interplay between many physical, chemical and biological processes. They are spatially heterogeneous in their material properties. Environmental data, especially below the surface, are hardly available and expensive to acquire. Thus, simulations are uncertain. They require real-time calibration and statistical concepts to support risk assessment and decision making.
Our Integrative and Interactive Simulation Approach
We unite uncertain simulations, data assimilation, optimisation and risk assessment within a single integrative, transferable and computationally efficient approach. It provides an interactive framework for different application tasks, such as calibration, prediction, design and control under uncertainty. We demonstrate our achievements towards Interactive Environmental Engineering with an example featuring carbon dioxide (CO2) injection into deep geologic formations to mitigate global warming. Assessing the potentials and risks of this technology as an interim solution requires to predict the involved multi-scale, multi-physical processes, quantify uncertainties, perform robust design and control of injection strategies, and to visualize and communicate the results at the science-policy interface.
Key ingredient 1: Multi-Physics, Multi-Scale
- CO2 leakage to the atmosphere:
complex high-performance simulation
A highly complex simulation challenge
Carbon capture and storage (CCS) has been proposed as an interim technology to reduce CO2 emissions. The storage and subsurface flow of CO2 after injection is governed by complex and non-linear multi-physics, multi-scale laws: instable multiphase-flow, phase transitions (fluid-gas-super-critical), dissolution into water, rock deformation, cracking, geochemistry, temperature effects, etc.
CCS requires highly developed simulation tools
We develop efficient and adaptive discretization schemes and numerical algorithms for multi-physical and multi-scale processes. The resulting codes are scalable to future high-performance computing architectures and equipped with total error control for accurate yet robust simulation.
Key ingredient 2: Model Reduction
- Squeezing a large model into a small
box: Projection onto a smart polynomial
Blind perfection comes at a high price
Current numerical simulation models for the multiphase flow and transport processes are inadequate for the repeated simulations required for uncertainty quantification, optimization, control and risk assessment. Even single simulation runs may require parallel high-performance computing. Reduced models can drastically speed up optimization, control and risk analysis. Still, they keep all relevant aspects of the original model with only a small, controlled error.
Response surface approach
We compress the reaction of complex simulations to parameter changes into a simple yet smart polynomial response surface [6] via the so-called arbitrary polynomial chaos expansion. All repetitive follow-up tasks evaluate the response surface within the blink of an eye.
Key ingredient 3: Risk Assessment
- How drastic is the hazard of CO2 leakage?
Probabilities evolving over time
Inconsiderate confidence in simulation is dangerous
For assessing the potential of CCS as interim solution to global warming, we should ideally know all possible reactions of the environment to CCS. Uncertain parameter values can change simulation outcomes by factors of 10, 100 or more. Therefore, our ability to quantify its uncertainties and risks play a key role and may even be more important that detailed numerical perfection of simulation codes.
Knowing the unknown
Our reduced models allow applying accurate and holistic methods for uncertainty quantification, and using them in probabilistic risk assessment. This way, we can predict the extent likelihood of benefits and damages we inflict on the environment and provide them as input to decision making.
Key ingredient 4: Robust Design
- Stay clear of undesired risks: well-chosen
safety margins and robustness
Our history proves: even high-tech can fail
CCS should be implemented such that even improbable dangers stay below acceptable risk levels. For example, one could choose the injection rate and depth to avoid geomechanical cracking at 99% safety level. The probability of failure and negative impacts will depend on the interplay between controllable engineering aspects and uncertain aspects of the system.
Optimize with rational safety margins
Robust design directly accounts for uncertainties and failure probabilities. This way, it can minimize risks during operation. Our proposed integrative approach simply includes design variables into the response surface. It assures optimization while guaranteeing that the known risks remain below a chosen acceptable level. Our optimized monitoring strategies help to identify and reduce residual risks.
Key ingredient 5: Science to Policy
- Simulators have more tasks than
simulating: Communication with all
stakeholders
Social impact
Research on CCS is inseparable from social dimensions: consumer behaviour and population growth, technological development and economical/ecological aspects, sustainability and risk acceptance, as well as opinion making and legislation. Without adequate visualization and communication, simulations results in politics easily turn into a double-edged sword, because they can be misunderstood dangerously.
Bridge to decision makers
Simulations should not be understood as “truth-generating machines”. Decision makers often underestimate the role of uncertainties in environmental simulations. This is why SimTech investigates the process of communicating simulations towards policy-makers. Our visualization methods facilitate to explore graphically and interactively possible CCS scenarios and their environmental impacts, including uncertainties.
Demonstrator: Interactive Optimisation of CCS
Our demonstrator shows simulation results for pressure and saturation of CO2 injected into the subsurface. We look at a geological system with known geometrical types of structures, but with uncertain material properties. The demonstrator combines all the key ingredients explained before:
- Thanks to model reduction, you can set the simulation input parameters with your mouse in real time. You can influence both uncertain material parameters and controllable system variables.
- Our 3D visualisation exploits the architecture of modern graphic cards. This way, your eyes perceive a smooth reaction to your simulation input.
- Optionally, you can leave individual parameter values unspecified. Then, you see the simulation result averaged over all possible values of the unspecified parameters, while you can still modify all other parameters.
- You can also have the standard deviation displayed, a measure for the uncertainty due to unknown parameter values.
- Try it yourself: adjust the injection variables such that the pressure in the system nowhere exceeds a critical value that you chose for yourself.
Our demonstrator illustrates, how the methods developed by SimTech allow performing risk analyses and robust design in real-time. Even for complex multi-scale, multi-physics environmental systems, they help to make the entire process intuitive and clear to the user.
Directly the demonstrator of the vision "Environmental Engineering"
Contributions to the vision "Environmental Engineering"