Our Methods

We develop methods for decision support that combine technology and social sciences.

Despite being increasingly considered essential to the success of waste management and disposal strategies as well as of large energy and infrastructure projects, the integration of social and technical dimensions has been limited due to a lack of dedicated methods. Such integration effort encounters at least three main challenges:

  • How to compensate technical and social performances of proposed solutions;
  • How to compare the technical performance of solutions in different social and environmental contexts;
  • How to make decisions under large uncertainties and conflicting values about the impact of proposed solutions.

Our cross-disciplinary methods respond to these challenges by helping to better manage uncertainty, reduce conflict, improve models’ integration, and increase institutional trust.

Performance evaluation

The socio-technical multi-criteria evaluation (STMCE) method is used for the performance comparison of alternatives for environmental remediation, waste management strategies, energy systems and large infrastructures. Specifically, this method can be applied to many decision problems at the back-end of the nuclear fuel cycle with socio-technical implications, particularly, (i) the selection of sites for interim storage of spent nuclear fuel; (ii) the selection of sites for disposal of low- and intermediate-level radioactive waste; (iii) the selection of remediation strategies for radioactively contaminated sites; and (iv) the selection of decommissioning strategies for nuclear power plants.

The multi-criteria evaluation provides an ordinal ranking of alternatives based on a list of criterion measurements. This method can handle quantitative, qualitative or both types of information about both technical and social dimensions of analysis—and their combination. The evaluation matrix may include crisp, stochastic or fuzzy measurements of the performance of an alternative with respect to an evaluation criterion.

For instance, when comparing sites for a repository in very different geologic settings one cannot use the same geochemical factors to compare their performance. This is because sites that are in different host rocks will not necessarily rely on the same retardation concepts. Therefore, host-rock-specific criteria do not allow the direct comparison of the technical suitability of sites with different geologic settings. A multi-scale representation of disposal systems allows the comparison of host-rock-specific repository designs at the level of their main components and processes (e.g., geological barriers, geochemical processes); whereas, their technical suitability is determined for a specific set of indicators and criteria. In this context, the multi-scale, multi-criteria performance evaluation seeks to rank all potential sites according to their level of fulfillment of safety functions.

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Conflict management

The STMCE method above can be extended to the analysis of social impacts and conflict management. The social impact analysis provides an ordering of alternatives based on the assessment of their impact on concerned socio-economic actors. The social impact matrix may include fuzzy uncertainty on assessments of impacts based on linguistic variables. In conflict management, the STMCE method supports the search for compromise solutions based on a coalition formation process.

Like for performance evaluation, the STMCE method for conflict management can be used in the contexts of environmental remediation, waste management strategies, energy systems and large infrastructures.

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Integrated assessment

The multi-scale integrated assessment method is used as a discussion and decision support tool by generating multi-scale indicators of sustainability. It was originally developed for the management of resources and was later extended to energy supply systems and nuclear waste disposal systems.

In resource management, the theoretical framework of the societal and ecosystem metabolism approach is based on analyzing the flows (e.g. food, energy, water, money) entering the system (e.g. a society), which are used to maintain and reproduce the set of structural and functional compartments of the system, as well as the resulting products coming out of it (e.g. fuels, electricity, drinkable water, revenues) which are required to express different socio-economic functions. That is, societal and ecological metabolism is the socio-economic process that involves the transformation of energy and materials for the production of goods and services, analogous to an organism that breaks down food and turns it into physical work.

In energy, the multi-scale integrated analysis approach is also used for assessing the viability and desirability of alternative energy systems and energy transition scenarios. Specifically, it cross checks information between the expected benchmarks of the energetic metabolic pattern (top-down assessment) and the expected performance of the energy-supply sector (bottom-up assessment). This robust analysis of energy systems in relation to the whole society makes it possible to study the implications of possible adjustments on both the supply or the demand side.

In nuclear waste management, the multi-scale integrated analysis approach provides a ‘metabolic’ representation to geological disposal systems. This representation allows one to account for the technical complexity of disposal systems in relation to their broader societal context. Such integrated formalism improves the overall understanding of the complexity of disposal systems and their policy requirements by connecting technical solutions with societal constraints.

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Uncertainty analysis

In decision making using computational models, adequate assessment of uncertainty and sensitivity must be conducted so that the predictions from the results of a computational model can be applied to real-world problems. Especially, uncertainty quantification and sensitivity analysis can help significantly in estimating, analyzing, and reducing uncertainties in the predictions of the radioactive waste management systems.

In uncertainty quantification (UQ), imprecision of the model prediction is estimated, analyzed and, if possible, reduced. Then, a sensitivity analysis (SA) identifies the influence of the different sources of uncertainty on the variability of the model output. State-of-the-art UQ methods can efficiently measure this uncertainty and the results of SA can bring new insights and understanding of its sources and treatment. However, frequently the main challenge in applying UQ is the high computational cost of its methods. A solution consists in building a metamodel that produces an approximate output in a significantly reduced computational time. Such multi-scale modelling method offers a promising approach in support of the safety case for the site selection and repository design of geological disposal systems.

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Sensitivity auditing

In repository design, epistemic uncertainties arise when projecting coupled geophysical and geochemical processes over large temporal and spatial scales. These uncertainties limit the ability to predict the long-term behavior of the repository because of the unavoidable lack of knowledge about future geological conditions. The “safety case” approach to decision has been developed to specifically address the issue of evaluating the long-term performance of a geologic repository in the face of such large uncertainty. Rather than focusing on models’ predictions, the safety case approach focuses on the level of confidence in the suitability of the site that must be sufficient to maintain political and public support during the overall process from site selection to repository closure. The safety case is therefore iteratively updated and revised as new data are gathered about the site.

As part of the statement of confidence supporting the safety case, there must be a qualitative and systematic appraisal of the different technical, methodological, societal and epistemological dimensions of uncertainty. Moreover, any quantitative assessment of uncertainty using models must start by defining clearly and unambiguously all hypotheses (e.g., uncertainties on all parameters), a priori. These two aspects of the management of uncertainty can be achieved by applying procedures of multi-dimensional uncertainty assessment and sensitivity auditing to the technical analyses supporting the safety case.

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