Why Do You Buy: Reducing Fashion Consumption Together through Reflection

Climate change has made us all aware of the urgent need for change. We know that governments, companies, and even us have a role to play in countering its effects. Sustainable consumer behavior usually involves things like eating less meat and cutting down on single-use plastics. However, what many people don’t realize is that the stuff we own,...

Reverse bias degradation of CIGS solar cells

Living With Data

The research and design hypothesize how data centers can complement the urban environment rather than make a negative impact, both environmentally and spatially. Data centers consume and produce a variety of valuable flows, ranging from electricity, cooling/heating and water use. The aim of the research is to discover whether it is possible to...

Assessment criteria for inter-organizational collaboration in interconnected infrastructure projects

Purpose: Societies depend on interconnected infrastructures that are becoming more complex over the years. Multi-disciplinary knowledge and skills are essential to develop modern infrastructures, requiring close collaboration of various infrastructure owners. To effectively manage and improve inter-organizational collaboration (IOC) in...

Employee Perspectives on Risk Management in a Construction Company

In addition to the tools and techniques available, project risk management also depends on the attitudes of people in an organisation, how the available tools are used, and how the procedures are followed. Therefore, efforts to improve the project risk management capacity of organisations may fail if the diversity of people (characters, traits...

Towards Circular ICUs: Circular Intubations as a Catalyser for Systemic Change

This project aims to reduce the environmental impact of the Intensive Care Unit (ICU) of the Erasmus Medical Center (EMC). Systemic design research was executed to map the current waste flow created by the ICU. Literature review, interviews and observations were performed to gather information about the healthcare protocols, hospital procurement...

Multi-Robot Local Motion Planning Using Dynamic Optimization Fabrics

In this paper, we address the problem of real-time motion planning for multiple robotic manipulators that operate in close proximity. We build upon the concept of dynamic fabrics and extend them to multi-robot systems, referred to as Multi-Robot Dynamic Fabrics (MRDF). This geometric method enables a very high planning frequency for high...

Time Series Analysis of Nonlinear Head Dynamics Using Synthetic Data Generated with a Variably Saturated Model

The performance of time series models is assessed using synthetic head series simulated with a numerical model that solves Richards' equation for variably saturated flow. Heads were simulated in a homogeneous unconfined aquifer between two parallel canals; measured daily precipitation and potential evaporation are specified at the land...

Bio-Based Plastics in Product Design: The State of the Art and Challenges to Overcome

Replacing fossil-based feedstock with renewable alternatives is a crucial step towards a circular economy. The bio-based plastics currently on the market are predominantly used in single-use applications, with remarkably limited uptake in durable products. This study explores the current state of the art of bio-based plastic use in durable...

Stirrer design for improving fluidization of cohesive powder: A time-resolved X-ray study

Stirring has been recognized in the literature as a promising technique for facilitating fluidization of cohesive powders, via inputting additional energy to counteract interparticle forces. However, the influence of operating conditions and stirrer configurations on flow behavior remains largely unknown, which impedes the practical...

Learning Reduced-Order Mappings between Functions: An Investigation of Suitable Inputs and Outputs

Data-driven approaches are a promising new addition to the list of available strategies for solving Partial Differential Equations (PDEs). One such approach, the Principal Component Analysis-based Neural Network PDE solver, can be used to learn a mapping between two function spaces, corresponding to a PDE. However, the practical limitations of...