Design and experimental investigation of a herringbone grooved gas bearing supported turbocharger

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Rigid body interactions are fundamental to numerous scientific disciplines, but remain challenging to simulate due to their abrupt nonlinear nature and sensitivity to complex, often unknown environmental factors. These challenges call for adaptable learnin ...

Fuel cells are considered one of the most efficient and environmental-friendly technologies available for converting chemical energy into electricity and heat, and considered a key technology to close the hydrogen cycle. In particular, combined heat and po ...

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

Modern machine learning (ML) models are capable of impressive performances. However, their prowess is not due only to the improvements in their architecture and training algorithms but also to a drastic increase in computational power used to train them.|S ...

This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...

We introduce a computational pipeline for simulating and designing C-shells, a new class of planar-to-spatial deployable linkage structures. A C-shell is composed of curved flexible beams connected at rotational joints that can be assembled in a stress-fre ...

Hermetic, small-scale turbo compressors supported on gas-lubricated bearings and driven by high-speed electric motors represent a promising technology to increase the efficiency of domestic heat pumps and air conditioners. Moreover, thanks to the oil-free ...

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

The sense of touch can provide a robot with a wealth of information about the contact region when interacting with an unknown environment. Nevertheless, utilizing touch information to plan exploration paths and adjust robot posture to improve task efficien ...

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

Detailed single neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools are dedicated to the reproduction of a small set of specific ...

Many transportation markets are characterized by oligopolistic competition. In these markets customers, suppliers and regulators make decisions that are influenced by the preferences and the decisions of all other agents. In particular, capturing and under ...

Design exploration is a creative process that consists of the incremental generation of design candidates. Supported by digital means or not, the process handles the ill-structured nature of design and allows creativity to flourish through diversity of des ...

Designing optimal soft modular robots is difficult, due to non-trivial interactions between morphology and controller. Evolutionary algorithms (EAs), combined with physical simulators, represent a valid tool to overcome this issue. In this work, we investi ...

Machine intelligence greatly impacts almost all domains of our societies. It is profoundly changing the field of mechanical engineering with new technical possibilities and processes. The education of future engineers also needs to adapt in terms of techni ...

Biological flapping wing fliers operate efficiently and robustly in a wide range of flight conditions and are a great source of inspiration to engineers. The unsteady aerodynamics of flapping wing flight are dominated by large-scale vortical structures tha ...

In this paper, we provide a Banach-space formulation of supervised learning with generalized total-variation (gTV) regularization. We identify the class of kernel functions that are admissible in this framework. Then, we propose a variation of supervised l ...

Design and experimental investigation of a herringbone grooved gas bearing supported turbocharger

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Integrating Physics and Topology in Neural Networks for Learning Rigid Body Dynamics

Role and Opportunities of Gas bearing supported Turbomachinery in small-scale SOFC-CHP systems

A ride time-oriented scheduling algorithm for dial-a-ride problems

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm

C-shells: Deployable Gridshells with Curved Beams

Brine-to-water heat pump test system for small-scale oil-free turbo compressors

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

Online active and dynamic object shape exploration with a multi-fingered robotic hand

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Universal and adaptive methods for robust stochastic optimization

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

A universal workflow for creation, validation and generalization of detailed neuronal models

Optimization and equilibrium problems with discrete choice models

Policy-based Exploration of Equilibrium Representations (PEER): A topology grammar for generative conceptual structural design

Seeking Quality Diversity in Evolutionary Co-design of Morphology and Control of Soft Tensegrity Modular Robots

Automated Design: A Journey Across Modelling, Optimization, and Education

Phenomenology and scaling of optimal flapping wing kinematics

Multikernel Regression with Sparsity Constraint