How To Make A Science Experiment More Reliable
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Designing Complexity: The Methodology and Practice of Systems Oriented Design
Author: Birger Sevaldson
language: en
Publisher: Common Ground Research Networks
Release Date: 2022-11-20
This book addresses one of the most pressing issues of our time: How can we design for, with, and in service of the complex world we live in? How can we be useful as designers in a rapidly changing world due to technological, political, and social processes, as well as climate change and nature destruction? Designers have some beneficial skills for planning with complex systems in mind, yet some old habits need to be overcome. Design's traditional purpose and role has been to solve problems, find order, organize, and simplify. Yet, the concept of designing complexity goes against these established beliefs because complexity cannot be designed away. So, instead, we present ways to live with, influence, and benefit from complex systems. There is no one "right" way presented in this book. Instead, many experiences, approaches, and perspectives are collected and presented. The process this book offers is a methodology called Systems Oriented Design (SOD). SOD is a design methodology and practice primarily geared toward understanding and working with complex systems. Several systems theories influence it, yet it remains true to its origin, the core of designing. SOD is a living and adaptable methodology. Though it is based on design thinking and design methodology, it is easily adapted and applied by anybody working with complex change processes.
The Aesthetics of Scientific Experiments
The relationship between aesthetics and science has begun to generate substantial interest. However, for the most part, the focus has been on the beauty of theories, and other aspects of scientific practice have been neglected. This book offers a novel perspective on aesthetics in experimentation via ten original essays from an interdisciplinary group comprised of philosophers, historians of science and art, and artists. The collection provides an analysis of the concept of beauty in the evaluation of experiments. What properties do practising experimenters value? How have the aesthetic properties of scientific experiments changed over the years? Secondly, the volume looks at the role that aesthetic factors, including negative values such as ugliness, as well as experiences of the sublime and the profound, play in the construction of an experiment and its reception. Thirdly, the chapters provide in-depth historical case studies from the Royal Society, which also allows for a study of the depiction of scientific experiment in artworks, as well as contemporary examples from the Large Hadron Collider and cases of experiments designed by artificial intelligence. Finally, it offers an exploration of the commonalities between how we learn from experiments on the one hand and the cognitive value of artworks on the other. The Aesthetics of Scientific Experiments will be of interest to researchers and advanced students working in philosophy and history of science, philosophy and history of art, as well as practising scientists and science communicators.
Designed Experiments for Science and Engineering
Designed Experiments for Science and Engineering is a versatile and overarching toolkit that explores various methods of designing experiments for over 20 disciplines in science and engineering. Designed experiments provide a structured approach to hypothesis testing, data analysis, and decision‐making. They allow researchers and engineers to efficiently explore multiple factors, interactions, and their impact on outcomes, ultimately leading to better‐designed processes, products, and systems across a wide range of scientific and engineering disciplines. Each discipline covered in this book includes the key characteristics of the steps in choosing and executing the experimental designs (one factor, fractional factorial, mixture experimentation, factor central composite, 3‐factor + central composite, etc.) and reviews the various statistical tools used as well as the steps in how to utilize each (standard deviation analysis, analysis of variance [ANOVA], relative standard deviation, bias analysis, etc.). This book is essential reading for students and professionals who are involved in research and development within various fields in science and engineering, such as mechanical engineering, environmental science, manufacturing, and aerospace engineering.