Yan Liu – författare

The Material Point Method: A Continuum-Based Particle Method for Extreme Loading Cases systematically introduces the theory, code design, and application of the material point method, covering subjects such as the spatial and temporal discretization of MPM, frequently-used strength models and equations of state of materials, contact algorithms in MPM, adaptive MPM, the hybrid/coupled material point finite element method, object-oriented programming of MPM, and the application of MPM in impact, explosion, and metal forming.

Recent progresses are also stated in this monograph, including improvement of efficiency, memory storage, coupling/combination with the finite element method, the contact algorithm, and their application to problems.

Modern Chinese for Heritage Beginners aims to serve as a stepping-stone for Chinese heritage language learners’ future Chinese learning, inspiring them to reflect on their identities, learn Chinese American history, and embrace their cultural heritage.

The book starts with talking about individuals and families and then expands to the Chinese and Asian American communities in the U.S. and eventually to the entire American society, all from the unique perspective of Chinese American students. Taking a macro approach that builds learners’ literacy skills on their initial abilities in speaking and listening, each lesson starts with listening and speaking activities and then moves to reading and writing. The content complexity and language difficulty are balanced to present rich content that matches students’ critical thinking abilities in a language appropriate for their literacy level. Lively and humorous language makes the book a joy to read. Each lesson has a conversation and an essay to expose students to informal and formal registers. Moreover, authentic tasks are designed to facilitate students’ language output, following the three modes of communication promoted by the American Council on Teaching Foreign Languages: interpersonal, interpretive, and presentational.

This theme-based Chinese textbook is written for high school and college-level Chinese heritage language learners.

Modern Chinese for Heritage Beginners aims to serve as a stepping-stone for Chinese heritage language learners’ future Chinese learning, inspiring them to reflect on their identities, learn Chinese American history, and embrace their cultural heritage.

The book starts with talking about individuals and families and then expands to the Chinese and Asian American communities in the U.S. and eventually to the entire American society, all from the unique perspective of Chinese American students. Taking a macro approach that builds learners’ literacy skills on their initial abilities in speaking and listening, each lesson starts with listening and speaking activities and then moves to reading and writing. The content complexity and language difficulty are balanced to present rich content that matches students’ critical thinking abilities in a language appropriate for their literacy level. Lively and humorous language makes the book a joy to read. Each lesson has a conversation and an essay to expose students to informal and formal registers. Moreover, authentic tasks are designed to facilitate students’ language output, following the three modes of communication promoted by the American Council on Teaching Foreign Languages: interpersonal, interpretive, and presentational.

This theme-based Chinese textbook is written for high school and college-level Chinese heritage language learners.

Demonstrates how to solve reliability problems using practical applications of Bayesian models

This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding.

Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more. 

Practical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance. 

Demonstrates how to solve reliability problems using practical applications of Bayesian models

This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding.

Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more. 

Practical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance. 

This book constitutes the refereed proceedings of the 25th International Conference on DNA Computing and Molecular Programming, DNA 25, held in Seattle, WA, USA, in August 2019.

The 12 full papers presented were carefully selected from 19 submissions. The papers cover a wide range of topics relating to biomolecular computing such as algorithms and models for computation on biomolecular systems; computational processes in vitro and in vivo; molecular switches, gates, devices, and circuits; molecular folding and self-assembly of nanostructures; analysis and theoretical models of laboratory techniques; molecular motors and molecular robotics; information storage; studies of fault-tolerance and error correction; software tools for analysis, simulation, anddesign; synthetic biology and in vitro evolution; and applications in engineering, physics, chemistry, biology, and medicine.

• Clean energy technologies, such as biomass, solar, wind, geothermal, nuclear including SMRs, hydrogen, etc.

• Renewable energy resources to reduce the consumption of traditional fossil fuels

• Emerging technologies for renewable energy harvesting, conversion, and storage

• New concepts or devices for energy generation, conversion, and distribution

• Waste heat recovery and other industrial energy efficient technologies

• Energy education and energy regulation

• Scale-up, stability, and life-cycle analysis of energy technologies and improvement of existing energy-intensive processes

• Theory and simulation in energy harvesting, conversion, and storage

• Design, operation, and optimization of processes for energy generation (e.g., carbon capture) and conversion of energy carriers

• Energy efficiency improvement in process engineering (e.g., for biomass conversion and improved combustion) and electrical engineering (e.g., for power conversion and developing smart grids)

• Thermo-electric/electrolysis/photo-electrolysis/fundamentals of PV

• Emission control, CO2 capture, and conversion

• Carbon sequestration techniques

• CO2 and other greenhouse gas reduction metallurgy in ferrous (iron & steel making and forming), non-ferrous and reactive metals including critical rare-earth metals

• Sustainability and life cycle assessment of energy systems

• Thermodynamics and modelling for sustainable metallurgical processes

• ''Smart cool materials'' for urban heat island mitigation (such as cool roof infrared reflecting material, and low-temperature heat absorbers for use in air conditioner condensers - like ''endothermic materials'')

• Methodologies for reducing the cost of energy materials production

• Circular economy and developing resource efficiency model for cutting down the transport from remote places

• Materials extraction and processing steps for enhancing energy efficiencies in batteries, supercapacitors, and energy efficient cells

• Foundational industry (metals-alloys, chemicals, refractories, cement) and energy economy and role of mineral extraction