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Granular Computing
Granular computing focuses on formalizing information granules and unifying them to create a coherent methodological and developmental environment for intelligent system design and analysis. This innovative book presents the unified principles of granular computing along with its comprehensive algorithmic framework and design practices. It explores key concepts and formalisms as well as applications. It also emphasizes the need to consider information granularity as an important design asset that helps in the construction of more realistic models of real-world systems and in facilitating collaborative pursuits of system modeling.
eBook
Robust design optimization under dependent random variables by a generalized polynomial chaos expansion
New computational methods are proposed for robust design optimization (RDO) of complex engineering systems subject to input random variables with arbitrary, dependent probability distributions. The methods are built on a generalized polynomial chaos expansion (GPCE) for determining the second-moment statistics of a general output function of dependent input random variables, an innovative coupling between GPCE and score functions for calculating the second-moment sensitivities with respect to the design variables, and a standard gradient-based optimization algorithm, establishing direct GPCE, single-step GPCE, and multi-point single-step GPCE design processes. New analytical formulae are unveiled for design sensitivity analysis that is synchronously performed with statistical moment analysis. Numerical results confirm that the proposed methods yield not only accurate but also computationally efficient optimal solutions of several mathematical and simple RDO problems. Finally, the success of conducting stochastic shape optimization of a steering knuckle demonstrates the power of the multi-point single-step GPCE method in solving industrial-scale engineering problems.
Journal Article
A computational method to aid the design and analysis of single cell RNA-seq experiments for cell type identification
Background
The advent of single cell RNA sequencing (scRNA-seq) enabled researchers to study transcriptomic activity within individual cells and identify inherent cell types in the sample. Although numerous computational tools have been developed to analyze single cell transcriptomes, there are no published studies and analytical packages available to guide experimental design and to devise suitable analysis procedure for cell type identification.
Results
We have developed an empirical methodology to address this important gap in single cell experimental design and analysis into an easy-to-use tool called SCEED (Single Cell Empirical Experimental Design and analysis). With SCEED, user can choose a variety of combinations of tools for analysis, conduct performance analysis of analytical procedures and choose the best procedure, and estimate sample size (number of cells to be profiled) required for a given analytical procedure at varying levels of cell type rarity and other experimental parameters. Using SCEED, we examined 3 single cell algorithms using 48 simulated single cell datasets that were generated for varying number of cell types and their proportions, number of genes expressed per cell, number of marker genes and their fold change, and number of single cells successfully profiled in the experiment.
Conclusions
Based on our study, we found that when marker genes are expressed at fold change of 4 or more, either Seurat or SIMLR algorithm can be used to analyze single cell dataset for any number of single cells isolated (minimum 1000 single cells were tested). However, when marker genes are expected to be only up to fold change of 2, choice of the single cell algorithm is dependent on the number of single cells isolated and rarity of cell types to be identified. In conclusion, our work allows the assessment of various single cell methods and also aids in the design of single cell experiments.
Journal Article
Building structures
\"This new edition continues its legacy as the reference of choice for architects studying contemporary issues and design practices for building structures by taking a conceptual approach that foregos complicated mathematics. Looking at the role of the structure as a building subsystem, it offers the fundamentals of computational methods for design of wood, steel, and reinforced concrete structures, along with new material such as discussion of the LRFD method of design. Profusely illustrated with new case studies, this go-to guide is perfect for non-engineers to understand and visualize structural design\"-- Provided by publisher.
Book
Digital Twin-Based Analysis and Optimization for Design and Planning of Production Lines
With the increasing dynamic nature of customer demand, production, product, and manufacturing design changes have become more frequent. Moreover, inadequate validation during the manufacturing design phase may result in additional issues, such as process redesign and layout reallocation, during the operation phase. Therefore, systems that can pre-validate and allow accurate and reliable analysis in the manufacturing design phase, as well as apply and optimize variations in production lines in real time, are required. Previously, digital twin (DT) has been studied a lot in product design and facility prognostics and management fields. Research on the system framework leading to DT utilization and optimization and analysis through DT in complex manufacturing systems with continuous processes such as production lines is insufficient. In this study, a system based on a DT and simulation results is developed; this system can reflect, analyze, and optimize dynamic changes in the design of processes and production lines in real time. First, the framework and application of the proposed system are designed. Subsequently, optimization methodologies based on heuristics and reinforcement learning (RL) are developed. Finally, the effectiveness and applicability of the proposed system are verified by implementing an actual DT application at a real manufacturing site.
Journal Article
Seismic analysis and design using the endurance time method
\"The endurance time method (ETM) is a seismic analysis procedure in which intensifying dynamic excitations are used as the loading function, and it provides many unique benefits in the design of structures. It can largely reduce the computational effort needed for the response history analysis of structures. This aids in the practical application of response history-based analysis in problems involving very large models and/or requiring numerous analyses to achieve optimal design goals. A single response history analysis through ETM provides an estimate of the system response at the entire range of seismic intensities of interest, thus making it ideal for applications such as seismic risk assessment, life-cycle cost analysis, and value-based seismic design. Conceptual simplicity also makes ETM a useful tool for preliminary response history analysis of structural systems. Features: Presents full coverage of the subject from basic concepts to advanced applied topics. Provides a coherent text on endurance time excitation functions that are essential in endurance time analysis. Seismic Analysis and Design using the Endurance Time Method serves as a comprehensive resource for students, researchers, and practicing structural engineers who want to familiarize themselves with the concepts and applications of the endurance time method (ETM) as a useful tool for dynamic structural analysis\"-- Provided by publisher.
Book
A Safety-Focused System Architecting Framework for the Conceptual Design of Aircraft Systems
To reduce the environmental impact of aviation, aircraft manufacturers develop novel aircraft configurations and investigate advanced systems technologies. These new technologies are complex and characterized by electrical or hybrid-electric propulsion systems. Ensuring that these complex architectures are safe is paramount to enabling the certification and entry into service of new aircraft concepts. Emerging techniques in systems architecting, such as using model-based systems engineering (MBSE), help deal with such complexity. However, MBSE techniques are currently not integrated with the overall aircraft conceptual design, using automated multidisciplinary design analysis and optimization (MDAO) techniques. Current MDAO frameworks do not incorporate the various aspects of system safety assessment. The industry is increasingly interested in Model-Based Safety Assessment (MBSA) to improve the safety assessment process and give the safety engineer detailed insight into the failure characteristics of system components. This paper presents a comprehensive framework to introduce various aspects of safety assessment in conceptual design and MDAO, also considering downstream compatibility of the system architecting and safety assessment process. The presented methodology includes specific elements of the SAE ARP4761 safety assessment process and adapts them to the systems architecting process in conceptual design. The proposed framework also introduces a novel safety-based filtering approach for large system architecture design spaces. The framework’s effectiveness is illustrated with examples from applications in recent collaborative research projects with industry and academia. The work presented in this paper contributes to increasing maturity in conceptual design studies and enables more innovation by opening the design space while considering safety upfront.
Journal Article