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OptiY
OptiY is a design environment software that provides modern optimization strategies and state of the art probabilistic algorithms for uncertainty, reliability, robustness, sensitivity analysis, data-mining and meta-modeling. Features OptiY is an open-source, multidisciplinary design environment, which provides direct and generic interfaces to many CAD/CAE-systems and house-intern codes. Furthermore, a complex COM-interface and a user-node with predefined template are available so that user can self-integrate extern programs for ease of use. The insertion of any system to an arbitrary process chain is very easy using the graphical workflow editor. Collaborating different simulation model classes is possible as networks, finite-element-method, multi-body-system, material test bench etc. Data mining Data mining is the process of extracting hidden patterns from data. Data mining identifies trends within data that go beyond simple data analysis. Through the use of sophisticated ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Surrogate Model
A surrogate model is an engineering method used when an outcome of interest cannot be easily measured or computed, so a model of the outcome is used instead. Most engineering design problems require experiments and/or simulations to evaluate design objective and constraint functions as a function of design variables. For example, in order to find the optimal airfoil shape for an aircraft wing, an engineer simulates the airflow around the wing for different shape variables (length, curvature, material, ..). For many real-world problems, however, a single simulation can take many minutes, hours, or even days to complete. As a result, routine tasks such as design optimization, design space exploration, sensitivity analysis and ''what-if'' analysis become impossible since they require thousands or even millions of simulation evaluations. One way of alleviating this burden is by constructing approximation models, known as surrogate models, ''metamodels'' or ''emulators'', that mimic th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
List Of Numerical Analysis Software
Listed here are notable end-user computer applications intended for use with numerical or data analysis: Numerical-software packages General-purpose computer algebra systems Interface-oriented Language-oriented Historically significant * Expensive Desk Calculator written for the TX-0 and PDP-1 The PDP-1 (''Programmed Data Processor-1'') is the first computer in Digital Equipment Corporation's PDP series and was first produced in 1959. It is famous for being the computer most important in the creation of hacker culture at Massachusetts ... in the late 1950s or early 1960s. * S is an (array-based) programming language with strong numerical support. R is an implementation of the S language. See also References {{DEFAULTSORT:Numerical Analysis Software Lists of software Mathematics-related lists *Software ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Failure Mode And Effects Analysis
Failure mode and effects analysis (FMEA; often written with "failure modes" in plural) is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects. For each component, the failure modes and their resulting effects on the rest of the system are recorded in a specific FMEA worksheet. There are numerous variations of such worksheets. An FMEA can be a qualitative analysis, but may be put on a quantitative basis when mathematical failure rate models are combined with a statistical failure mode ratio database. It was one of the first highly structured, systematic techniques for failure analysis. It was developed by reliability engineers in the late 1950s to study problems that might arise from malfunctions of military systems. An FMEA is often the first step of a system reliability study. A few different types of FMEA analyses exist, such as: * Functional * Design * Process Sometime ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer System Optimization Software
A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations ( computation) automatically. Modern digital electronic computers can perform generic sets of operations known as programs. These programs enable computers to perform a wide range of tasks. A computer system is a nominally complete computer that includes the hardware, operating system (main software), and peripheral equipment needed and used for full operation. This term may also refer to a group of computers that are linked and function together, such as a computer network or computer cluster. A broad range of industrial and consumer products use computers as control systems. Simple special-purpose devices like microwave ovens and remote controls are included, as are factory devices like industrial robots and computer-aided design, as well as general-purpose devices like personal computers and mobile devices like smartphones. Computers power the Internet, which l ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Robust Parameter Design (RPD)
A robust parameter design, introduced by Genichi Taguchi, is an experimental design used to exploit the interaction between control and uncontrollable noise variables by robustification—finding the settings of the control factors that minimize response variation from uncontrollable factors. Control variables are variables of which the experimenter has full control. Noise variables lie on the other side of the spectrum. While these variables may be easily controlled in an experimental setting, outside of the experimental world they are very hard, if not impossible, to control. Robust parameter designs use a naming convention similar to that of FFDs. A 2''(m1+m2)-(p1-p2)'' is a 2-level design where ''m1'' is the number of control factors, ''m2'' is the number of noise factors, ''p1'' is the level of fractionation for control factors, and ''p2'' is the level of fractionation for noise factors. Consider an RPD cake-baking example from Montgomery (2005), where an experimenter wants ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pareto Optimal
Pareto efficiency or Pareto optimality is a situation where no action or allocation is available that makes one individual better off without making another worse off. The concept is named after Vilfredo Pareto (1848–1923), Italian civil engineer and economist, who used the concept in his studies of economic efficiency and income distribution. The following three concepts are closely related: * Given an initial situation, a Pareto improvement is a new situation where some agents will gain, and no agents will lose. * A situation is called Pareto-dominated if there exists a possible Pareto improvement. * A situation is called Pareto-optimal or Pareto-efficient if no change could lead to improved satisfaction for some agent without some other agent losing or, equivalently, if there is no scope for further Pareto improvement. The Pareto front (also called Pareto frontier or Pareto set) is the set of all Pareto-efficient situations. Pareto originally used the word "optimal" for th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multiobjective Optimization
Multi-objective optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, multiattribute optimization or Pareto optimization) is an area of multiple criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multi-objective optimization has been applied in many fields of science, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives. Minimizing cost while maximizing comfort while buying a car, and maximizing performance whilst minimizing fuel consumption and emission of pollutants of a vehicle are examples of multi-objective optimization problems involving two and three objectives, respectively. In practical problems, there can be more than three objectives. For a nontrivial multi-objective optimization problem, no single soluti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fatigue (material)
In materials science, fatigue is the initiation and propagation of cracks in a material due to cyclic loading. Once a fatigue crack has initiated, it grows a small amount with each loading cycle, typically producing striations on some parts of the fracture surface. The crack will continue to grow until it reaches a critical size, which occurs when the stress intensity factor of the crack exceeds the fracture toughness of the material, producing rapid propagation and typically complete fracture of the structure. Fatigue has traditionally been associated with the failure of metal components which led to the term metal fatigue. In the nineteenth century, the sudden failing of metal railway axles was thought to be caused by the metal ''crystallising'' because of the brittle appearance of the fracture surface, but this has since been disproved. Most materials, such as composites, plastics and ceramics, seem to experience some sort of fatigue-related failure. To aid in predicting t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Probabilistic Design
Probabilistic design is a discipline within engineering design. It deals primarily with the consideration of the effects of random variability upon the performance of an engineering system during the design phase. Typically, these effects are related to quality and reliability. Thus, probabilistic design is a tool that is mostly used in areas that are concerned with quality and reliability. For example, product design, quality control, systems engineering, machine design, civil engineering (particularly useful in limit state design) and manufacturing. It differs from the classical approach to design by assuming a small probability of failure instead of using the safety factor. Designer's perspective When using a probabilistic approach to design, the designer no longer thinks of each variable as a single value or number. Instead, each variable is viewed as a probability distribution. From this perspective, probabilistic design predicts the flow of variability (or distributions) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Proprietary Software
Proprietary software is software that is deemed within the free and open-source software to be non-free because its creator, publisher, or other rightsholder or rightsholder partner exercises a legal monopoly afforded by modern copyright and intellectual property law to exclude the recipient from freely sharing the software or modifying it, and—in some cases, as is the case with some patent-encumbered and EULA-bound software—from making use of the software on their own, thereby restricting his or her freedoms. It is often contrasted with open-source or free software. For this reason, it is also known as non-free software or closed-source software. Types Origin Until the late 1960s computers—large and expensive mainframe computers, machines in specially air-conditioned computer rooms—were usually leased to customers rather than sold. Service and all software available were usually supplied by manufacturers without separate charge until 1969. Computer vendors ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sensitivity Analysis
Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis should be run in tandem. The process of recalculating outcomes under alternative assumptions to determine the impact of a variable under sensitivity analysis can be useful for a range of purposes, including: * Testing the robustness of the results of a model or system in the presence of uncertainty. * Increased understanding of the relationships between input and output variables in a system or model. * Uncertainty reduction, through the identification of model input that cause significant uncertainty in the output and should therefore be the focus of attention in order to increase robustness (perhap ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
