Advanced Finite Element Simulation With MSC Mar...
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Advanced Finite Element Simulation with MSC Mar...
Graduates with the Master of Science in Aerospace Engineering look forward to career opportunities at higher levels of responsibility. The areas of opportunities include, but are not limited to, mechanics of aerospace vehicles and structures, composite materials, finite element analysis, experimental and computational fluid dynamics, flight dynamics and control of aerospace vehicle, advanced control theory and its application to aerospace system, and electric propulsion. Opportunities for aerospace engineers continue to develop with the rapid expansion of the knowledge base.
MSC Software is one of the ten original software companies and a global leader in helping product manufacturers to advance their engineering methods with simulation software and services. As a trusted partner, MSC Software helps companies improve quality, save time, and reduce costs associated with design and test of manufactured products. Academic institutions, researchers, and students employ MSC's technology to expand individual knowledge as well as expand the horizon of simulation. MSC Software employs 1,100 professionals in 20 countries. For additional information about MSC Software's products and services, please visit: www.mscsoftware.com.
Tissue engineering strategies can be relevant for cartilage repair and regeneration. A collagen matrix was functionalized with the addition of poly-lactic-co-glycolic acid microcarriers (PLGA-MCs) carrying a human Transforming Growth Factor β1 (hTFG-β1) payload, to provide a 3D biomimetic environment with the capacity to direct stem cell commitment towards a chondrogenic phenotype. PLGA-MCs (mean size 3 0.9 μm) were prepared via supercritical emulsion extraction technology and tailored to sustain delivery of payload into the collagen hydrogel for 21 days. PLGA-MCs were coseeded with human Bone Marrow Mesenchymal Stem Cells (hBM-MSCs) in the collagen matrix. Chondrogenic induction was suggested when dynamic perfusion was applied as indicated by transcriptional upregulation of COL2A1 gene (5-fold; p p p p p
The courses aim to equip you with the knowledge and practical skills necessary to tackle challenges in an industrial or research environment. It will provide you with new theoretical insights and the ability to apply them to real-world problems, using advanced analysis tools and industry standard software.
As a post-doctoral research fellow at the National University of Ireland Galway under the supervision of Prof. Peter McHugh, Ellen used computational methods (finite element analysis) to analyze drug release kinetics from implantable devices
This programme enables students to develop advanced knowledge of civil engineering and associated engineering and scientific disciplines such as structural dynamics, sustainable building design, transport, fluids, geotechnics, water and drainage, environmental and coastal engineering, planning and construction. It provides students with the awareness of the context in which engineering operates, and equips them with the transferable skills necessary for careers in industry and research.
The M.S.C.E. degree provides a student with the opportunity to earn the advanced degree with either coursework only or research thesis options. Students must have an accredited first degree in engineering or complete a list of prerequisite engineering coursework. The M.S.C.E. with thesis is a research-oriented degree in which the student writes, as a major part of the degree requirements, a thesis that defines, examines, and reports in depth on a subject area relevant to Civil Engineering. Both the thesis and non-thesis options prepare graduates for careers with governmental agencies, nongovernmental organizations (NGOs), or private industry and firms involved in Civil Engineering planning, design, or policy.
This article discusses that computer-based technologies have greatly influenced the way design engineers work. The first technological innovation was the use of high-powered personal computers. With PCs, engineers had access to high-speed applications of computer-aided design software right at their own desks. Personal computers took the place of rulers and pencils. The second innovation, he said, is the advancing capability of PCs to function as supercomputers, crunching numbers much faster than formerly possible. By taking advantage of this technology, engineers untrained in a mathematical application such as finite element analysis can run an FEA software program that performs calculations automatically and will shave weeks off the design process. Hothouse uses the Spatial technology to repair CAD models brought in from outside sources and to translate CAD files the company sends to its suppliers, collaborators, and clients. Before Hothouse began sending CAD files to the online service, company employees spent days repairing or rebuilding files on their own. Sometimes suppliers or clients that received Hothouse CAD files had to do similar work on their end.
In this blog, we demonstrate the deployment, performance, and price comparisons of Simcenter Nastran for three finite element analysis (FEA) based use cases on Amazon Web Services (AWS) high performance computing (HPC) clusters. Simcenter Nastran is a FEA application by Siemens, used across multiple engineering disciplines such as aerospace, automotive, electronics, and medical devices for solving problems related to linear and nonlinear structural analysis, acoustics, aeroelasticity, thermal analysis, and optimization.
FEA simulations are compute- and memory-intensive, and engineers have traditionally run these simulations using on-premises workstations. However, using on-premises resources can limit engineers in terms of available capacity and scale. By running these types of workloads on AWS, engineers can take advantage of on-demand pricing, elastic capacity, and the latest technology to help them maximize their investment in FEA codes, without the challenges of managing on-premises infrastructure.
Simcenter Nastran application is Message Passing Interface (MPI) enabled, and runs on an HPC system consisting of building blocks using the AWS services highlighted below. FEA analyses involve large matrix operations, and hence typically require hardware with high clock speed processors, high memory, and throughput. For that purpose, we have chosen Amazon EC2 memory-optimized R5 and compute-optimized C5 On-Demand Instances for this workload. Amazon EC2 R5d instances, with up to 32 physical cores, are based on 3.1 GHz Intel Skylake-SP or Cascade Lake processors. Amazon EC2 C5d.18xlarge instances, with 36 physical cores, are based on 3.4 GHz Intel Skylake-SP processors. These instances are powered by the AWS Nitro System, an advanced hypervisor technology, and support high memory requirements for FEA solvers, resulting in increased performance and reduced latency. Amazon EBS drive with 50-GB storage is attached to the head node for storing the application files.
AWS ParallelCluster, an AWS supported open-source cluster management tool, is used to deploy and manage HPC clusters. You can specify the desired cluster components such as instance types, storage, etc. in a single text file, and can deploy an HPC cluster within 15 minutes. Version 2.10 is used for this blog. AWS Cloud9, a cloud-based integrated development environment (IDE) that lets you collaborate to write, run, and debug code in a browser, is used for securely accessing the HPC cluster via secure shell (SSH). Note, that any IDE should work for this purpose. Amazon Elastic Block Store (Amazon EBS) is an easy to use, durable, high-performance, block-storage service that can be used for FEA workloads, which are both throughput and data intensive. Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. The simulation results, to and from the HPC clusters, are stored in Amazon S3 buckets for further use or further archival to Amazon S3 Glacier.
Test case 1 involves computing mode-sets for a block of solid elements. The model has 5.4 million elements and 6.0 million DoF, and is computed with the Lanczos method. The best performance was achieved on Amazon EC2 r5d.8xlarge instance with SMP = 16 (Figure 2).
While the test cases described above represent the typical problem sizes run by our customers, we also performed FEA simulations on a relatively large model representing an airplane wing with 148 million elements, and 600 million DoF. We selected an Amazon EC2 high-memory instance, the x1.32xlarge with 64 physical cores and 1.9-TB memory for this workload. For this large case, Simcenter Nastran performed about 12% faster on the x1.32xlarge instance compared to that on Amazon EC2 r5d.16xlarge instance. Given the considerably higher instance costs, use the Amazon EC2 x1.32xlarge instance for running your urgent, time-sensitive simulations only. 041b061a72