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White Paper on Equivalent Relationships of Physical Quantities presents a bold rethinking of classical mechanics. Inspired by Einstein's insight into the equivalence of mass and energy, this work introduces a complementary principle: the equivalence between force and power. Challenging the longstanding notion that static forces do no work, it argues that all forces--including static ones--are associated with continuous energy consumption. Through dimensional analysis, theoretical modeling, and practical implications, the paper offers a unified framework for understanding both dynamic and…mehr

Produktbeschreibung
White Paper on Equivalent Relationships of Physical Quantities presents a bold rethinking of classical mechanics. Inspired by Einstein's insight into the equivalence of mass and energy, this work introduces a complementary principle: the equivalence between force and power. Challenging the longstanding notion that static forces do no work, it argues that all forces--including static ones--are associated with continuous energy consumption. Through dimensional analysis, theoretical modeling, and practical implications, the paper offers a unified framework for understanding both dynamic and static systems. Developed through a unique collaboration between human insight and artificial intelligence, this white paper marks a new step in the scientific exploration of energy, force, and structure. It is ideal for physicists, engineers, philosophers of science, and anyone interested in the foundational questions of modern physics.
Autorenporträt
Keying Guan is a retired professor and independent researcher with a lifelong dedication to foundational physics. After a distinguished academic career in China, he relocated to the United States in 2008 and continued his independent exploration of static force and energy. His blog essays on ScienceNet.cn laid the groundwork for a new principle--the force-power equivalence--as a conceptual complement to Einstein's mass-energy equivalence. His work emphasizes clarity, dimensional rigor, and the reevaluation of classical assumptions. This white paper, co-developed with ChatGPT, exemplifies the transformative potential of human-AI collaboration in modern physics.