Focusing on a pivotal transitional period, this book explores the evolution of Chinese science fiction, highlighting its significance as a precursor to the genre's growing global prominence in the twenty-first century. It provides insights into the cultural and literary shifts that have shaped contemporary Chinese sci-fi, offering a comprehensive understanding of its development and impact on the global stage.
Set against the backdrop of a changing China in the 1990s, the narrative follows Hua, an only child raised by an intellectual father and a spirited mother. At nineteen, she leaves her small town by the Yangtze River to explore the world, embarking on a remarkable journey across four countries over two decades. The story highlights her personal growth and the cultural experiences that shape her identity as she navigates life away from home.
The science of mathematical modelling and numerical simulation is generally accepted as the third mode of scienti? c discovery (with the other two modes being experiment and analysis), making this ? eld an integral component of c- ting edge scienti? c and industrial research in most domains. This is especially so in advanced biomaterials such as polymeric hydrogels responsive to biostimuli for a wide range of potential BioMEMS applications, where multiphysics and mul- phase are common requirements. These environmental stimuli-responsive hydrogels are often known as smart hydrogels. In the published studies on the smart or stimu- responsive hydrogels, the literature search clearly indicates that the vast majority are experimental based. In particular, although there are a few published books on the smart hydrogels, none is involved in the modelling of smart hydrogels. For the few published journal papers that conducted mathematical modelling and numerical simulation, results were far from satisfactory, and showed signi? cant d- crepancies when compared with existing experimental data. This has resulted in ad hoc studies of these hydrogel materials mainly conducted by trial and error. This is a very time-consuming and inef? cient process, and certain aspects of fun- mental knowledge are often missed or overlooked, resulting in off-tangent research directions.
The science of mathematical modelling and numerical simulation is generally accepted as the third mode of scienti? c discovery (with the other two modes being experiment and analysis), making this ? eld an integral component of c- ting edge scienti? c and industrial research in most domains. This is especially so in advanced biomaterials such as polymeric hydrogels responsive to biostimuli for a wide range of potential BioMEMS applications, where multiphysics and mul- phase are common requirements. These environmental stimuli-responsive hydrogels are often known as smart hydrogels. In the published studies on the smart or stimu- responsive hydrogels, the literature search clearly indicates that the vast majority are experimental based. In particular, although there are a few published books on the smart hydrogels, none is involved in the modelling of smart hydrogels. For the few published journal papers that conducted mathematical modelling and numerical simulation, results were far from satisfactory, and showed signi? cant d- crepancies when compared with existing experimental data. This has resulted in ad hoc studies of these hydrogel materials mainly conducted by trial and error. This is a very time-consuming and inef? cient process, and certain aspects of fun- mental knowledge are often missed or overlooked, resulting in off-tangent research directions.
Bei der Entwicklung eines Optimierungsverfahrens für die Planung des Lkw-Transports müssen zahlreiche Anforderungen berücksichtigt werden, darunter Ladereihenfolge, Stapelbarkeit und Sicherung der Ladeobjekte sowie die effiziente Raumausnutzung. Die Rechenzeit der Optimierung muss begrenzt sein, um praktische Anwendbarkeit zu gewährleisten. Zunächst werden Kennzahlen wie Achslasten, Fixierungsgrad und Kippsicherheitsgrad in mathematischer Form dargestellt. Nach einer Analyse bekannter Verfahren werden Strategien für die Anordnung der Ladeobjekte entwickelt, die in verschiedene Gruppen unterteilt werden: Verarbeitung der Entladestellen, optimale Stapelung nach Stapelbarkeit und Anordnung der Stapelungen im Laderaum. Die Anordnung erfolgt in zwei Stufen: Zuerst werden optimale Stapelungen erzeugt, gefolgt von deren Anordnung im Laderaum. Die zweite Stufe umfasst eine Eröffnungs- und Verbesserungsphase, um füllgradoptimierte Lösungen zu erreichen. Die Optimierung berücksichtigt die Gesamtnutzlast und Achslasten des Transportmittels. Der Fixierungsgrad in der Zielfunktion maximiert die Ladungssicherung, während der Kippsicherheitsgrad eine quantitative Bewertung der Transportsicherung ermöglicht. Die entwickelten Strategien werden in einen Algorithmus umgesetzt, der die Anforderungen der Automobilindustrie erfüllt. Tests zeigen die Leistungsfähigkeit des Algorithmus, der die Planung des Lkw-Transports revolutioniert und auf Erfahr