ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

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Gamma-ray Spectroscopy in Low-Power Nuclear Research Reactors

Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari

Gamma-ray spectroscopy is an effective technique for radioactive material characterization, routine inventory verification, nuclear safeguards, health physics, and source search scenarios. Gamma-ray spectrometers typically cannot be operated in the immedia ...

MDPI2024

Gamma noise to non-invasively monitor nuclear research reactors

Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari, Pavel Frajtag, Tom Mager

Autonomous nuclear reactor monitoring is a key aspect of the International Atomic Energy Agency’s strategy to ensure nonproliferation treaty compliance. From the rise of small modular reactor technology, decentralized nuclear reactor fleets may strain the ...

Nature Research2024

Learning to Remove Cuts in Integer Linear Programming

Volkan Cevher, Grigorios Chrysos, Efstratios Panteleimon Skoulakis

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

2024

Neutron-Gamma Noise Measurements in a Zero-Power Reactor Using Organic Scintillators

Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari

Noise measurements in light water reactor systems aid in generating validation data for integral point kinetic parameter predictions and generating monitoring parameters for reactor safety and safeguards. The CROCUS zero-power reactor has been used to supp ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Intra-pin Reaction Rate Measurements in the CROCUS Experimental Reactor

Andreas Pautz, Vincent Pierre Lamirand, Mathieu Hursin, Oskari Ville Pakari, Thomas Jean-François Ligonnet, Tom Mager

In response to the need for validating high-fidelity deterministic neutronics solvers capable of providing pin-resolved neutron flux distributions, intra-pin reaction rates measurements were performed in the CROCUS experimental reactor. A specially designe ...

2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Stability: a search for structure

Wouter Jongeneel

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

EPFL2024

Oxidation processes and me

Urs von Gunten

This publication summarizes my journey in the field of chemical oxidation processes for water treatment over the last 30+ years. Initially, the efficiency of the application of chemical oxidants for micropollutant abatement was assessed by the abatement of ...

Pergamon-Elsevier Science Ltd2024

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