Analatom, Applied Research Laboratory Penn State University, and University of California Irvine propose to apply modern concepts from simulation, corrosion modeling, and control theory along with Prognostics and Health Management (PHM) in the development of an endto-end, prognostics-based Additive Manufacturing (AM) materials assessment architecture. The project team will consider four potential levels of implementation that includes molecular dynamics simulation of material corrosion and cracking defects, AM advanced statistical process control and monitoring, enhancing end-use items with corrosion, strain sensors and operational environment assessment techniques. Selection of appropriate applied levels architecture will be dependent on the desired target application. Emphasis will be placed on developing a flexible computational framework that incrementally learns optimal parameters and discerns parameter sets that lead to degradation profiles. An approach for a Reliability-Centered AM Computational Design Framework (RCAM CDF) focused on selective laser melt (SLM) AM processes for metallic components has been developed. This design framework initially includes minimum part geometry for a load bearing coupon structure, with defect types and densities induced by design of the AM build fabrication process, followed by laser Computed Tomography (CT) inspection of the components, with subsequent in situ structural monitoring sensors (corrosion, strain) to record the accelerated lifetime and fatigue testing. Existing designs, associated design tools appropriate for design, materials, processes, standards and data management systems already exist. These designs already have associated failure modes, fault analysis tools and fault isolation manuals referenced to actual designs. Introducing new tools that attempt to unilaterally replace existing design tools will inhibit RCAM CDF adoption rate. An alternate approach that Analatom recommends uses associative memory linking data exported from design tools, materials, processes, standards, and data management systems across the entire US Navy enterprise creating a library of reference Additive Manufacturing designs. The designs would be based on original designs modified for Additive Manufacturing. Preliminary proof has been demonstrated that this approach can capture and find "seeded" print defects correlating to scan images taken during build. The associative memory image based "defect" scanner has been able similar "defect regions" corresponding to small simulated corrosive pits.

Since August 2010, Resensys wireless SenSpot tilt and strain sensors were deployed to monitor a highway bridge in Maryland. Similar installations were performed in bridges in the US, Canada, and Indonesia. Signal analyses concluded important observations about the response of the bridge bearings to change of temperature. In some instances, the change in the strain exceeded 30 microstrains, e.g., due to the bridge rehabilitation work. The decision parameters about the state of a structure were fused to produce the structural integrity knowledge to be used for predictive diagnostics. Using this method, the monitoring system can predict rupture, crack, yielding or generally any signals before the collapse of a structure or any member damage before it happens. Finally, Resensys is working with Anal-atom, Inc, and other third-party OEMs in the development of an Onboard SHM Data Aggregator Module (OSDAM) platform to manage and control access to multiple SHM Sensor Systems.

This paper presents an experiment adapting linear polarization resistance-based corrosion sensors, originally developed for aerospace applications, to measure the corrosion rate of API 5L ERW grade-B steel natural gas line pipe using micro-sized linear polarization resistance (mu LPR) sensors made from the same alloy and grade steel. Sensors were installed under a 15 mil coating of fusion-bonded epoxy, at various proximities to a 1/8 inch defect introduced at a weld joint and along the pipe seam. After sensor installation the pipe was buried in an controlled environment with soil amended to a pH of five. This environment was held at a temperature above 35 degrees C while soil moisture content was modulated between wet and dry cycles, each lasting 7 days. LPR and environmental measurements were sampled at 5 min intervals. Post processing was performed to convert the LPR measurements to a surface-loss. Comparisons made in the data showed API 5L ERW grade-B steel natural gas pipelines were highly susceptible to corrosion along the seam, with all sensors showing activity in this region early in the experiment. Sensors adjacent to a weld joint began to display evidence of corrosion more slowly. These results verify the ability of mu LPR sensors to measure corrosion activity under protective coatings in underground environments.

This paper presents a micro-sized Linear Polarization Resistance (μLPR) corrosion sensor for Structural Health Management (SHM) applications. The μLPR sensor is based on conventional macro-sized Linear Polarization Resistance (LPR) sensors with the additional benefit of a reduced form factor making it a viable and economical candidate for remote corrosion monitoring of high value structures, such as buildings, bridges, or aircraft. An experiment was conducted with eight μLPR sensors and four test coupons to validate the performance of the sensor. The results demonstrate the effectiveness of the sensor as an efficient means to measure corrosion. The paper concludes with a brief description of a typical application where the μLPR is used in a bridge cable.

Handheld Portable Maintenance Support Tool (PMST) incorporates microcontroller unit providing a wireless interface between a sensor node network, consisting of Analatom micro-LPR corrosion sensors combined with off-the-shelf sensors, and portable computer databases for high value asset monitoring and matériel management. PMST will be able to provide the user real-time capability to evaluate health status and operability of future MDA hardware including structures and vehicles such as Launch Platform, and Future Interceptor. This assessment capability provides early warning of structural and component deterioration or failure traditionally encountered during time of use. PMST system results in reduced maintenance, maintenance costs, downtime, and vulnerability of MDA’s stockpile, while increasing inventory condition-awareness and battle readiness. Clear benefits are improvements in safety and security while expanding field readiness and operational capacity. Future extensions to PMST system will provide new prognostics, readiness predictions, matériel inventory management, and mobilization capabilities.

The aim of this project is the development of advanced software modeling tools for data mining, maintenance support, and structural health monitoring prognostics. The project will develop new modeling, optimization tools and algorithm concepts that provide database search and correlations facilitating intelligent decision making processes for maintenance, repair and overhaul work practices and schedules. Ultimately, such a support tool will act upon current databases, meta-data and repair practices to arrive at considerable personnel, parts and other resource savings as well as shorter repair time horizons within the Maintenance, Repair, and Overhaul (MRO) environment. An aircraft maintenance and repair work scope optimizer, as a decision support tool, will utilize dynamic data, meta-data information and knowledge to provide the repair work force with a daily work package that accommodates contingencies via dynamic re-planning. The decision support tool will be orderly, repeatable and controlled using advanced AI techniques to identify associations within a dynamic information repository, the Information Cube.

Projected Hartree-Fock calculations involving both spin and orbital angular momentum projection are reported for the lowest 2P state of Li. The value 0.0679 a.u. is obtained for the spin-dipolar hyperfine structure term, in very good agreement with the experimental result of 0.0690 a.u. The energy is -7.36516 a.u. compared to the Hartree-Fock result of -7.36507 and the experimental energy of -7.41016 a.u.

: This project demonstrated innovative remote sensors (LPR sensors) the size of postage stamps which can provide instantaneous corrosion rate data from under a coating. These sensors were installed beneath a coating on a mission-critical metal structure roof in Okinawa, to detect the intrusion of moisture and predict the corrosion rates from the shifts in polarization resistance. With this real-time data capability, early detection of the need for maintenance on the structure can be determined and corrections made, extending the service life of the structure and lowering life-cycle cost. This technology is applicable to metal roofs, water tanks, fences or any metal structures that early detection of corrosion is needed to extend the life of the structure, avoid costly early replacement or avoid complete failure of the structure. Standard coupon tests and electrical resistance (ER) probes provide corrosion rates at a lower cost than the LPR sensors but not instantaneous rates as do the LPR sensors. Standard coupon and ER probes were demonstrated on this project for comparison to LPR corrosion rate data and to obtain atmospheric corrosion rates in this highly corrosive environment.

Analatom, Inc. is developing the Structural Health Monitoring (SHM) system using its Linear Polarization Resistance (LPR) corrosion sensors combined with a Texas Instruments MSP430 microprocessor for lower weight, lower power, higher sensitivity, and lower cost than conventional sensor systems. The system provides both strain and corrosion measurements in a package a few mils thick. This combination of data provides critical assessment of structural health, leading to prediction of failure. The MEMS sensors are permanently installed in a high-valued structure, such as a building, bridge or aircraft, and are connected to a data acquisition node. Data transmission and downloading uses a MaxStrearn ZigBee/IEEE 802.15.4 compliant chip for a wireless, self-organizing network that has low power requirements. The sensor network provides a low-cost, non-intrusive way to detect failures, or to signal ahead of time that preventative maintenance needs to be undertaken to prevent future more expensive replacement.Analatom, Inc. has developed the basic technology for a Portable Maintenance Support Tool (PMST). The device is unique and novel in that it uses a Micro Controller Unit in a handheld device to perform data analysis whilst maintaining a link with a Personal Computer based database for further support. The handheld prototype with a Liquid Crystal Display (LED) touch screen GUI takes readings from a variety of sensors and transfers the data wirelessly to a central PC hub. The handheld unit using the downloaded data from the sensor network can then provide a graphic display and additionally transfer those data to a workstation for further data analysis. Analatom, Inc. builds on its corrosion system platform (sensors, data acquisition unit, data storage) to develop a multiplexed system to obtain data from a variety of sensors, while further developing real time intelligent algorithms to monitor corrosion rates.

Analatom, Inc. is developing a Structural Health Monitoring system using its proprietary Linear Polarization Resistance corrosion sensors combined with a TI MSP430 microprocessor for lower weight, lower power, higher sensitivity, and lower cost than conventional sensor systems. The system provides both strain and corrosion measurements in a package a few mils thick. This combination of data can provide critical assessments of structural health, leading to prediction of failure. The MEMS sensors are permanently installed on a high-valued structure, such as a building, bridge or aircraft, and are connected to a data acquisition node. Data transmission and downloading will use a ZigBee wireless chip, a self-organizing network that has low power requirements. The sensor network provides a low-cost, non-intrusive way to detect failures, or to signal ahead of time that preventative maintenance needs to be undertaken to prevent more expensive replacement in the future. Corrosion Health Monitoring Systems and Prognostics are key elements in assuring the performance and reliability of high value, critical structures. Analatom has developed a multiplexed system that obtains data from a variety of sensors with real-time intelligent algorithms to detect, monitor and predict corrosion rates. Second generation Neural Networks have shown that total state event-shifts within non-linear systems can now be modeled, wherein concurrent, multiple and often interacting sensor signal signatures enhance and amplify this modeling process such that hidden interactions and element dependencies are clarified and understandable. Analatom has developed such a second generation Neural Network architecture whereby multiple and multi-layered element interactions can be evaluated, grouped and monitored. This enhancement now enables CBM monitoring and tracking to reflect local regions of negative impact which arise from multiple and interacting states of degradation.

This paper will describe the Structural Health Monitoring system that Analatom is developing. The technology builds on the well-established Analatom MEMS based sensors which provide both strain and corrosion measurements in a package a few mils thick. This combination of data provides critical assessment of structural health, leading to prediction of failure. The MEMS sensors are permanently installed in a high-valued structure, such as a building, bridge or aircraft, and are connected to a data acquisition node. The Analatom sensor nodes are connected into a mesh network which communicates wirelessly for efficient structural monitoring. The sensor nodes use the ZigBee wireless standard, which allows for low-powered operation, saving on battery power and resulting in long operating times in the field. The sensor network provides a low-cost, non-intrusive way to detect failures, or to signal ahead of time that preventative maintenance needs to be undertaken to prevent more expensive replacement in the future. Analatom has developed the basic technology for a Portable Maintenance Support Tool (PMST). The device is unique and novel in that it uses a Micro Controller Unit in a handheld device to perform data analysis whilst maintaining a link with a Personal Computer based database for further support. The handheld prototype with a Liquid Crystal Display (LED) touch screen GUI takes readings from a variety of sensors and transfers the data wirelessly to a central PC hub.

The goal is to build a three-dimensional diagnostic/prognostic imaging system that is specifically designed for Structural Health Monitoring. The technology builds on the well established Analatom, Inc. corrosion monitoring and strain gauge sensor technology. This system has been significantly improved in the development of a sensor network on representative structures that will produce data to be used for 3-D Imaging. Detail such as format, data types and stamping have been addressed and data produced by test frames will be used to develop the higher-level analysis functionality. In further work we will develop the imaging and prognostic algorithms that will be able to visually depict moisture exposure and impact damage. The ability to identify potential trouble spots will result in better resource allocation strategies and thereby improve planning.

Analatom Inc. in conjunction with the DSTO (Defence Science & Technology Organisation) has been developing a micro Linear Polarization Resistance (LPR) system for assessing the integrity of high value structures. The device operates on the principle that as a metal corrodes, the oxide formed effectively creates an anodic cell. Hence, if the metal can be separated into two sections, a potential and resistance can be measured between each section. These values can be used to compute the effective mass loss of the device. By matching the material properties of the device with that of the structure whose "health" is being monitored, it is possible to establish a corrosion rate of the structure. Previous research at DSTO has shown that such a system can be fabricated and operated on the micro scale. The task has now been to develop the device into a commercially viable system; it is this development that is examined in this paper. In the original system, a potentiostat is used to evaluate the device for data relating the mass loss during corrosion. This system is now replaced with simplified electronics to reduce both the cost and size of the device. Signal conditioning into the LPR is critical as potentials over 20mV across the terminals can be a source of corrosion of the device. Micro controllers and small board computers are used to run this signal conditioning process and the LPR interface circuit.

The problem addressed in this paper is the through-life, non-destructive monitoring of corrosion and disbonding damages in airframes. The concept presented here is to produce a MEMS smart sensor consisting of a number of small, independent, wireless sensors within the structure of the aircraft. The MEMS smart sensor can be installed during repair and in particular when the specific platform goes through a complete tear down during the Life Extension Program (LEP). The sensors are permanently installed and can be permanently monitored and contain bond degradation sensing elements and CMOS circuits. Each sensor has an independent address and can perform measurements and communicate over a true 2-wire bus to an external interface unit. US ( 09/501,798) and international (PCT/US00/03308) patent applications have been lodged for this technology.

Liquid n-tridecane (C13H28) chains confined between two parallel hard walls separated by 5.0 nm have been studied by Monte Carlo simulations, employing united CH2 atoms linked with fixed bond lengths and angles and continuously varying torsional angles subject to appropriate interaction energies. Molecules located in the central region are in remarkable agreement with ideal unperturbed chains. Significant influences of walls persist over a distance of ∼1.5 nm, exhibiting progressively less-dense and less-pronounced segmental layers of ∼0.4 nm thickness. Segmental orientations preferentially aligned along the surface are found only in the first layer, accompanied by little perturbations in the fraction of trans-conformations. Furthermore, nearly all the chain units in the first segmental layer adjacent to the walls belong to two-dimensional chains, and exhibit considerable orientational correlations between neighboring segments of different chains. The terminal portions of some of the molecules in the succeeding layer are also located in the first layer, thus increasing the fraction of methyl chain ends in contact with the walls. These findings match very closely the experimental results of surface forces and viscosities of liquid n-alkanes confined between two mica plates, measured as a function of the plate separation.

ChemInformVolume 21, Issue 42 Physical Organic Chemistry ChemInform Abstract: Molecular Arrangements and Conformations of Liquid n-Tridecane Chains Confined Between Two Hard Walls. M. VACATELLO, M. VACATELLO Almaden Res. Cent., IBM Res. Div., San Jose, CA 95120, USASearch for more papers by this authorD. Y. YOON, D. Y. YOON Almaden Res. Cent., IBM Res. Div., San Jose, CA 95120, USASearch for more papers by this authorB. C. LASKOWSKI, B. C. LASKOWSKI Almaden Res. Cent., IBM Res. Div., San Jose, CA 95120, USASearch for more papers by this author M. VACATELLO, M. VACATELLO Almaden Res. Cent., IBM Res. Div., San Jose, CA 95120, USASearch for more papers by this authorD. Y. YOON, D. Y. YOON Almaden Res. Cent., IBM Res. Div., San Jose, CA 95120, USASearch for more papers by this authorB. C. LASKOWSKI, B. C. LASKOWSKI Almaden Res. Cent., IBM Res. Div., San Jose, CA 95120, USASearch for more papers by this author First published: October 16, 1990 https://doi.org/10.1002/chin.199042040AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume21, Issue42October 16, 1990 RelatedInformation

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTChain conformations of polycarbonate from ab initio calculationsBernard C. Laskowski, Do Y. Yoon, Doug McLean, and Richard L. JaffeCite this: Macromolecules 1988, 21, 6, 1629–1633Publication Date (Print):June 1, 1988Publication History Published online1 May 2002Published inissue 1 June 1988https://pubs.acs.org/doi/10.1021/ma00184a018https://doi.org/10.1021/ma00184a018research-articleACS PublicationsRequest reuse permissionsArticle Views173Altmetric-Citations40LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts

Ab initio computational chemistry methods have been used to study the molecular structure of polymeric materials. We present here theoretical results for the barriers to internal rotation in several Polyalkylmethacrylate polymers. We also include the results of independent investigations of the backbone and side chain conformations. Our calculations quantitatively reproduce the experimentally determined relaxation energies. It appears that the original experimental assignments are not correct. However, our theoretical predictions are in agreement with the results of new sophisticated temperature dependent NMR experiments.