Publications associées à Combining Stochastic Optimization and Monte-Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

EPFL2024

The impacts of decarbonization pathways on Sustainable Development Goals in the European Union

Marc Vielle, Sigit Pria Perdana

Climate action to achieve the Paris Agreement should respect the United Nations Sustainable Development Goals. Here, we use an integrated assessment modelling framework comprising nine climate policy models and quantify the impacts of decarbonisation pathw ...

2024

Climate risk assessment of buildings: An analysis of operating emissions of commercial offices in Australia

Arianna Brambilla

Building climate risk assessment involves benchmarking a building's energy use intensity against decarbonisation pathways to mitigate the impacts on climate change. Various climate risk assessment tools and frameworks are used for commercial buildings in d ...

Elsevier Science Sa2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Robot Learning using Tensor Networks

Suhan Narayana Shetty

In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

EPFL2024

Impact of anthropogenic emission control in reducing future PM2.5 concentrations and the related oxidative potential across different regions of China

Yuan Yuan, Athanasios Nenes

Affected by both future anthropogenic emissions and climate change, future prediction of PM2.5 and its Oxidative Potential (OP) distribution is a significant challenge, especially in developing countries like China. To overcome this challenge, we estimated ...

Elsevier2024

A diversity-driven discovery of potential nanoporous materials for energy-related applications

Sauradeep Majumdar

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

EPFL2024

Robust optimization of control parameters for WEC arrays using stochastic methods

Edie Miglio, Tommaso Vanzan

This work presents a new computational optimization framework for the robust control of parks of Wave Energy Converters (WEC) in irregular waves. The power of WEC parks is maximized with respect to the individual control damping and stiffness coefficients ...

Journal of Computational Physics2023

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Jan Skaloud, Davide Antonio Cucci, Kenneth Joseph Paul

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

2023

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Christophe Ballif, Nicolas Würsch, Laure-Emmanuelle Perret Aebi, Marine Dominique Cauz

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

2023

RaFSIP: Parameterizing ice multiplication in models using a machine learning approach

Athanasios Nenes, Paraskevi Georgakaki

Accurately representing mixed-phase clouds (MPCs) in global climate models (GCMs) is critical for capturing climate sensitivity and Arctic amplification. Secondary ice production (SIP), can significantly increase ice crystal number concentration (ICNC) in ...

2024

Decision support for the design of integrated biorefineries

Julia Granacher

A shift from fossil-based energy and products to more sustainable alternatives is essential to reduce greenhouse gas emissions and associated climate change impacts. Biomass represents a promising alternative for providing fuels and carbon-based products w ...

EPFL2023

Stochastic adaptive resampling for the estimation of discrete choice models

Michel Bierlaire, Nicola Marco Ortelli, Matthieu Marie Cochon de Lapparent

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

2023

Quantitative Methods for Omnichannel Decision-Making

Andrey Vasilyev

Omnichannel retail has emerged as the new standard in today's commerce landscape, with retailers integrating their physical and online channels to enhance the customer shopping experience. However, such integration presents significant challenges for retai ...

EPFL2023

Synthesis Report on the Environmental Impacts of Polar Research and Logistics in the Polar Regions

Jérôme Chappellaz

Polar sciences are crucial to understand the effects of climate change. 6 out of 9 eco-tipping points identified by the IPCC are situated in the polar regions. Potential rising sea levels, altered weather patterns and changes in sea-currents are all connec ...

2023

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

Influence of future climate scenarios on the sizing of Building-Integrated Photovoltaics (BIPV) installations. Case study of a new research-center building in Switzerland

Sergi Aguacil Moreno

This paper analyzes the findings obtained when applying a multi-criteria performance-based method for sizing a BIPV installation considering different weather files, representing historical data (TMY; typical meteorological year) and prospective data (thre ...

2023

A multimodel analysis of post-Glasgow climate targets and feasibility challenges

Marc Vielle, Sigit Pria Perdana

The COP26 Glasgow process resulted in many countries strengthening their 2030 emissions reduction targets and announcing net-zero pledges for 2050–2070 but it is not clear how this would impact future warming. Here, we use four diverse integrated assessmen ...

2023

Demand-based operations of vehicle sharing systems

Selin Ataç

Vehicle sharing systems (VSSs) allow users to rent vehicles for a short period of time, in a more flexible and convenient manner compared to the traditional vehicle rental services. The long-term VSS subscription replaces the need for contract signing for ...

EPFL2023

Integration of Life Cycle Impact Assessment in Energy System Modelling

Manuele Domenico Margni, François Maréchal, Jonas Schnidrig, Justine Brun

The Paris agreement is the first-ever universally accepted and legally binding agreement on global climate change. It is a bridge between today’s and climate-neutrality policies and strategies before the end of the century. However, government and private ...

2023