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Mpact details
CEMAP
MPACT SPHINX MPAVE | The contents of this web-site can be accessed by going to the Contents Section. A report on a procedure to cap a leaking deep-sea oil pipe may be downloaded from here. Tornado Centrifuge You can see how it works by looking at the mid-section of the top like structure.
The
mixture is introduced through the square hole shown on the top right of the
diagram. The mixture is fed in tangential to the circumference. The rotary
motion forces the mixture to the wall. However since the specific gravity of
Gulf Oil is 0.95 and that of liquid methane is 0.5, the methane is forced
towards the center and since it is lighter than oil, it floats to the top. The
diagram shows the liquid methane collecting at the top in the shape of an
inverted hemisphere. Similarly, the oil flows to the bottom. Both liquids are
evacuated through riser pipes.This centrifuge has some good points to recommend
it for this application:-
Knowledge and Information Processing. The world of Science and Technology is circumscribed by Information and knowledge. The Internet has placed an expanding volume of data and information at the hands of everyone. A major task is to mine this information to inform our practice and enrich our view of our Research and Development. The tools we use here are what we would call a subset of the A.I.Tools (Tools of Artificial Intelligence.). These are the tools of Computational Linguistics, more specifically the tools of Natural Language processing. The main task is to turn unstructured text into structured information. This task involves several levels of semantic understanding so that the appropriate information can be extracted. These are discussed in ascending order of their complexity. 1. The simplest and most developed approach is that developed in the 1980-2000. Here the unstructured text is first parsed in a syntax free manner. Then the relevant data is found by a Named Entity Recognition, the defined relationships between the named entities allows a structured database to be built. (see wiki on Named Entity Recognition). MPACT offers a general purpose tool called Conceptual Dependency Entity Recognizer. (CDER now in Beta test). 2. The next level of information extraction combines syntax free parsing with semantic processing. This allows a more flexible definition of the Semantic Entities to be extracted. The Automatic Natural Language Abstraction Processing (ANLAP) program was developed for semantic level extraction. It was applied to extracting information from Radiation Leakage Reports in Nuclear Plants.[1] 3. The next level of information extraction requires the full semantic processing of the text. This tool is currently under development. An important reference on Planning Applied Module can be downloaded from here. Computer Aided Translation. Information also exist in other Languages and we would like to be able to extract information from text in other languages. In cases where the languages have similar grammatical structure, the NER techniques described under 1. can be performed with minor extensions and word level translations. However in our work on Radiation Leakage, one of the largest source of information is in Japanese. In our initial research we were not able to find a good translator that was capable of translating document level Japanese. The objective was to turn the Japanese text to English so that the ANLAP program could be used to extract the required information. We have developed the Japanese English Mapping (JEMAP) Computer Aided Translation Software. To place the work in a broader perspective, we note that the ability to translate written text from one language to another can satisfy many needs. For example to someone with little or no knowledge of Japanese, it can be very useful to acquire the meaning of a Japanese Document. It can open a window into the extensive scientific research published in Japan but not translated to English. To writers of Japanese not well-versed in English it can be the means to publishing in the English translation, often in learned publications. Most commercial Japanese to English translators are based on some form of semantic parsing.(see for example Bond [2]). The semantic natural language parsing is in its infancy and though quite powerful, it still has a problem handling compound long sentences. On the other hand context free parsing is a well established technique. Church et al [3] have demonstrated a general method of performing statistical syntax free parsing. The origins of JEMAP are based on the following observations:-
A translator is a complex piece of work. In order to do a good job, it is important to take advantage of any other available code that can be of use. This is the reason for calling it a Computer Aided Translator. The author makes no apology in including the necessary pieces of software as an integral part of JEMAP. It takes advantage of the following software :- 1. A Japanese word processor. In my case the NJStar word processor. The original text and all the dictionaries are based on *.txt copies of UTF8 unicode. 2. The Google Japanese English translator which does a good job in translating phrases, specially those that result from a conjugation of verbs that are not readily available in the dictionaries used. This translator appears to be based on the Honyaku translator by Toshiba[4]. It does not do a good job in translating compound sentences but serves well at the phrase level. 3. The executive writing version of WhiteSmoke [5] helps correct the grammar and spelling of the resulting English. It does a fair job of supplying the missing articles and plural forms in English. This is also supplemented by the spell checker in Microsoft Word. A better placement of articles and plurals is given in [2]. It is envisaged that the algorithm described in [2] will be implemented here in the future. Examples of JEMAP translations will be given here as they occur. Please address all enquiries to pedrovmarcal@gmail.com References.
We have also developed the Chinese English Mapping (CEMAP) Computer Aided Translation Software. The ability to translate written text from one language to another can satisfy many needs. For example to someone with little or no knowledge of Chinese, it can be very useful to acquire the meaning of a Chinese Document. It can open a window into the extensive scientific research published in China but not translated to English. To writers of Chinese not well-versed in English it can be the means to publishing in the English translation, often in learned publications. Most commercial Chinese to English translators are based on some form of semantic parsing. The problems of mapping the Chinese Language into English follows a similar process to that of mapping Japanese to English (some of the problems there has been discussed in Bond[1]).The semantic natural language parsing is in its infancy and though quite powerful, it still has a problem handling compound long sentences. On the other hand context free parsing is a well established technique. Church et al [2] have demonstrated a general method of performing statistical syntax free parsing. The origins of CEMAP are based on the following observations:-
A translator is a complex piece of work. In order to do a good job, it is important to take advantage of any other available code that can be of use. This is the reason for calling it a Computer Aided Translator. The author makes no apology in including the necessary pieces of software as an integral part of CEMAP. It takes advantage of the following software :- 1. A Chinese word processor. In my case the NJStar word processor. The original text and all the dictionaries are based on *.txt copies of UTF8 unicode. 2. The Google Chinese English translator which does a good job in translating phrases. This translator appears to be based on statistical processing of large volumes of translation.[5] It does not do a good job in translating verb tenses but serves well at the phrase level. 3. The executive writing version of WhiteSmoke [6] helps correct the grammar and spelling of the resulting English. It does a fair job of supplying the missing articles and plural forms in English. Alternately, one may use the grammar and spell checker in Microsoft Word. A better placement of articles and plurals is given in [1]. It is envisaged that the algorithm described in [1] will be implemented here in the future. Examples of CEMAP translations will be given here as they occur. Please address all enquiries to pedrovmarcal@gmail.com
References.
Verified and Validated Virtual Reality. The Research, Design, Development, Manufacture and Service of a Product is critically dependent on Computer Aided Engineering (CAE). This CAE is CAD based and its progress is tracked throughout its life cycle by a process known as Product Life-cycle Management (PLM). While PLM is implemented in a modern database, one of its most important function is to ensure that the application of CAE in all its forms results in the integrity of the product throughout its lifetime. The application of CAE is in turn dependent on its Verification and Validation (V & V). By Verification, we mean that the code and process used simulates the chosen model correctly. Whereas the chosen model is just an idealized simulation of physical reality, the Validation of our models is a determination that our model and process captures the essentials of the physical model. The Validation process is almost taken on trust. It relies on historical application and comparisons of simulations with experiment. In part it has been driven by the acknowledgement of the high cost of conducting experiments. These experiments in turn were mostly limited to ideal Laboratory conditions. Recent developments in the application of hand-held laser based strain measurements by Direct Measure Inc.(DMI) have given us an experimental tool that can measure the strains throughout the life of a product. The gauges use a standardized form of 2D laser markings. Strains may be measured at any point throughout the life of a product. The measurement of strains can be large and so we call these gauges the Green's Strain Rosette. The use of the Green's Strain Rosettes now can cost less than the comparable simulations and, in our view, introduces a paradigm shift where all critical simulations can and should be Verified and Validated. To this end , we have assembled a suite of tools that will help the analyst in applying CAE to the task at hand, determining the critical locations where the Green's Strain Rosettes should be applied and comparing the analytical results with experimental readings throughout the life of a product. In the following we summarize the tools that we can place in the analysts hands, we do not insist that our tools are the only available ones, but these are the tools that have been integrated and tested with a view to easy implementation of the V & V process. 1. DMI hand held laser reader and Green's Strain Rosettes.
Measurement of strains :- a) with loading. b) cumulative plastic strains (elastic-plastic). c) cumulative creep-strain (high temperature). d) Large Strains on Rubber. (vulcanized gauges). e) Composite materials. f) With filler smoothing of coarse grained materials such as wood and concrete. g) gauge lengths of 0.5 cms. e) Temperature compensated readings. 2. Pre and post- processing tools. a) NaviaEO, a standardized Navigation program from the Sekisui Corp. The program offers a standardized GUI for the analysis and documentation of CAE that is extremely useful in the early stages of design and planning of experiments. It is partly based on the MPAVE pre and post processor. b) MPAVE, a python based multi-physics pre and post processor. MPAVE is CAD based and has journaling and remote client support for calls from other programs written in a multiple number of languages. (XMLRPC protocol). MPAVE has a feature to compare experimental strain histories with the analytical results. MPAVE supports the MPACT program, the SPHINX program and the FEMAP neutral file format and the NASTRAN (in development) format. 3. CAE Simulation Tools. a) The Multi Physics Adaptive Computer Technology (MPACT) code is a general purpose nonlinear FEA code. It can be used to predict the behavior of most nonlinear situations and as such is a cost-effective tool for life cycle analysis. It is a good support tool for the V&V process. c) The Smooth Particle Hydrodynamic (SPHINX) code applies the SPH technology to the simulation of Fluid and Structural mechanics problems. Its an explicit method that is particularly suited to high strain simulationand Fluid Solid Interaction. Its applications usually take over in the range where the FEA method is challenged by large distortions or disassembly.
Our MissionProvide the tools and services for life cycle integrity in order to provide our users with a Verified and Validated Virtual Reality.
Company ProfileThe Company is made up of veterans of the Finite Element and Experimental Mechanics Community, with experience in the technology as well as the commercial side of the business. Dr. Pedro V. Marcal is the CEO and Chairman of the Board is a well known pioneer in nonlinear Finite Element Analysis. His thesis provided the first correlation between theory and experiment for low-cycle fatigue of complex shells. He was the Founder of MARC Corp. and the developer of the MARC general purpose nonlinear program. Dr. Bill Ranson, Director, is a recognized expert in the area of stress and fatigue analysis of mechanical systems. He established one of the three original manufacturing extension centers that has grown to 52 centers. These provide services to a base of 325,000 manufacturing companies. He is a founder of the Direct Measure Inc. Mr. Dom Barnabei, Director, is the founder and owner of Aegis Corp., he was an early adopter and marketer of the FEMAP, and CAEFEM programs. Mr. Nobuki Yamagata, Director, was the Manager of MARC Japan for 25 years and has extensive ties to the FEA Community in Japan. The Company is supported by a select and growing number of distributors with extensive experience of technical consulting in design and analysis. Further details can be found in the Distributor section. Mr. John Campbell, Campbell Consulting, Wisconsin, Tel. (262) 638 9157 Mr. Kelly Fetzer, Automated Connectors Holdings, L.P., Texas, Tel. (281) 830 1886 Dr. Ali Moazed, Design Analysis Assoc., Boston Tel. (508) 740 2540 Mr. Martin J. Walsh, Southeastern Design and Analysis Corp., Georgia Tel.(912) 247 8560
Contact InformationOur preferred method of contact is via our web-site and/or email. However, we are always pleased to hear from you in any way that you prefer.
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