24 research outputs found
Recommended from our members
Continuous-wave radar to detect defects within heat exchangers and steam generator tubes.
A major cause of failures in heat exchangers and steam generators in nuclear power plants is degradation of the tubes within them. The tube failure is often caused by the development of cracks that begin on the outer surface of the tube and propagate both inwards and laterally. A new technique was researched for detection of defects using a continuous-wave radar method within metal tubing. The experimental program resulted in a completed product development schedule and the design of an experimental apparatus for studying handling of the probe and data acquisition. These tests were completed as far as the prototypical probe performance allowed. The prototype probe design did not have sufficient sensitivity to detect a defect signal using the defined radar technique and did not allow successful completion of all of the project milestones. The best results from the prototype probe could not detect a tube defect using the radar principle. Though a more precision probe may be possible, the cost of design and construction was beyond the scope of the project. This report describes the probe development and the status of the design at the termination of the project
Recommended from our members
Statistical validation of engineering and scientific models : bounds, calibration, and extrapolation.
Numerical models of complex phenomena often contain approximations due to our inability to fully model the underlying physics, the excessive computational resources required to fully resolve the physics, the need to calibrate constitutive models, or in some cases, our ability to only bound behavior. Here we illustrate the relationship between approximation, calibration, extrapolation, and model validation through a series of examples that use the linear transient convective/dispersion equation to represent the nonlinear behavior of Burgers equation. While the use of these models represents a simplification relative to the types of systems we normally address in engineering and science, the present examples do support the tutorial nature of this document without obscuring the basic issues presented with unnecessarily complex models
Recommended from our members
Case study for model validation : assessing a model for thermal decomposition of polyurethane foam.
A case study is reported to document the details of a validation process to assess the accuracy of a mathematical model to represent experiments involving thermal decomposition of polyurethane foam. The focus of the report is to work through a validation process. The process addresses the following activities. The intended application of mathematical model is discussed to better understand the pertinent parameter space. The parameter space of the validation experiments is mapped to the application parameter space. The mathematical models, computer code to solve the models and its (code) verification are presented. Experimental data from two activities are used to validate mathematical models. The first experiment assesses the chemistry model alone and the second experiment assesses the model of coupled chemistry, conduction, and enclosure radiation. The model results of both experimental activities are summarized and uncertainty of the model to represent each experimental activity is estimated. The comparison between the experiment data and model results is quantified with various metrics. After addressing these activities, an assessment of the process for the case study is given. Weaknesses in the process are discussed and lessons learned are summarized
Recommended from our members
Application of multidisciplinary analysis to gene expression.
Molecular analysis of cancer, at the genomic level, could lead to individualized patient diagnostics and treatments. The developments to follow will signal a significant paradigm shift in the clinical management of human cancer. Despite our initial hopes, however, it seems that simple analysis of microarray data cannot elucidate clinically significant gene functions and mechanisms. Extracting biological information from microarray data requires a complicated path involving multidisciplinary teams of biomedical researchers, computer scientists, mathematicians, statisticians, and computational linguists. The integration of the diverse outputs of each team is the limiting factor in the progress to discover candidate genes and pathways associated with the molecular biology of cancer. Specifically, one must deal with sets of significant genes identified by each method and extract whatever useful information may be found by comparing these different gene lists. Here we present our experience with such comparisons, and share methods developed in the analysis of an infant leukemia cohort studied on Affymetrix HG-U95A arrays. In particular, spatial gene clustering, hyper-dimensional projections, and computational linguistics were used to compare different gene lists. In spatial gene clustering, different gene lists are grouped together and visualized on a three-dimensional expression map, where genes with similar expressions are co-located. In another approach, projections from gene expression space onto a sphere clarify how groups of genes can jointly have more predictive power than groups of individually selected genes. Finally, online literature is automatically rearranged to present information about genes common to multiple groups, or to contrast the differences between the lists. The combination of these methods has improved our understanding of infant leukemia. While the complicated reality of the biology dashed our initial, optimistic hopes for simple answers from microarrays, we have made progress by combining very different analytic approaches
Recommended from our members
Cross-language information retrieval using PARAFAC2.
A standard approach to cross-language information retrieval (CLIR) uses Latent Semantic Analysis (LSA) in conjunction with a multilingual parallel aligned corpus. This approach has been shown to be successful in identifying similar documents across languages - or more precisely, retrieving the most similar document in one language to a query in another language. However, the approach has severe drawbacks when applied to a related task, that of clustering documents 'language-independently', so that documents about similar topics end up closest to one another in the semantic space regardless of their language. The problem is that documents are generally more similar to other documents in the same language than they are to documents in a different language, but on the same topic. As a result, when using multilingual LSA, documents will in practice cluster by language, not by topic. We propose a novel application of PARAFAC2 (which is a variant of PARAFAC, a multi-way generalization of the singular value decomposition [SVD]) to overcome this problem. Instead of forming a single multilingual term-by-document matrix which, under LSA, is subjected to SVD, we form an irregular three-way array, each slice of which is a separate term-by-document matrix for a single language in the parallel corpus. The goal is to compute an SVD for each language such that V (the matrix of right singular vectors) is the same across all languages. Effectively, PARAFAC2 imposes the constraint, not present in standard LSA, that the 'concepts' in all documents in the parallel corpus are the same regardless of language. Intuitively, this constraint makes sense, since the whole purpose of using a parallel corpus is that exactly the same concepts are expressed in the translations. We tested this approach by comparing the performance of PARAFAC2 with standard LSA in solving a particular CLIR problem. From our results, we conclude that PARAFAC2 offers a very promising alternative to LSA not only for multilingual document clustering, but also for solving other problems in cross-language information retrieval
Recommended from our members
Wavenumbers for currents on infinite- and finite-length wires in a chiral medium
There is increasing interest in determining the electromagnetic properties of material media differing from free space and the effects thereof on the radiation, propagation, and scattering of electromagnetic fields. A material property of special present interest is that of chirality. Chirality manifests itself as a handedness'' wherein a chiral medium does not support propagation of a linearly-polarized plane wave, but which instead decomposes into two circularly-polarized waves that propagate at different speeds. Initial work in this area was devoted to developing various analytical solutions to some basic problems such as the Green's Dyadic for a point current source. Attention is now being increasingly devoted to using this early work for a variety of applications such as analyzing antennas in chiral media scattering from chiral objects; scattering from objects having chiral coatings; and reflection from planar chiral interfaces. The focus of the work described here is determining the wavenumbers (={minus}{alpha}{minus}j{beta}) of the current waves excited on wire antennas located in an infinite chiral medium using two complementary approaches. One is to use an extension of an existing computer model (NEC) that permits modeling of arbitrary wire objects located in an infinite chiral medium. The other is to develop a solution for an infinitely long cylindrical antenna also located in an infinite chiral medium. The latter canonical problem is of interest in its own right as well as providing a means for achieving mutual validation with the NEC model. 9 refs
Recommended from our members
High throughput instruments, methods, and informatics for systems biology.
High throughput instruments and analysis techniques are required in order to make good use of the genomic sequences that have recently become available for many species, including humans. These instruments and methods must work with tens of thousands of genes simultaneously, and must be able to identify the small subsets of those genes that are implicated in the observed phenotypes, or, for instance, in responses to therapies. Microarrays represent one such high throughput method, which continue to find increasingly broad application. This project has improved microarray technology in several important areas. First, we developed the hyperspectral scanner, which has discovered and diagnosed numerous flaws in techniques broadly employed by microarray researchers. Second, we used a series of statistically designed experiments to identify and correct errors in our microarray data to dramatically improve the accuracy, precision, and repeatability of the microarray gene expression data. Third, our research developed new informatics techniques to identify genes with significantly different expression levels. Finally, natural language processing techniques were applied to improve our ability to make use of online literature annotating the important genes. In combination, this research has improved the reliability and precision of laboratory methods and instruments, while also enabling substantially faster analysis and discovery
Recommended from our members
Systems assessment of water savings impact of controlled environment agriculture (CEA) utilizing wirelessly networked Sense•Decide•Act•Communicate (SDAC) systems.
Reducing agricultural water use in arid regions while maintaining or improving economic productivity of the agriculture sector is a major challenge. Controlled environment agriculture (CEA, or, greenhouse agriculture) affords advantages in direct resource use (less land and water required) and productivity (i.e., much higher product yield and quality per unit of resources used) relative to conventional open-field practices. These advantages come at the price of higher operating complexity and costs per acre. The challenge is to implement and apply CEA such that the productivity and resource use advantages will sufficiently outweigh the higher operating costs to provide for overall benefit and viability. This project undertook an investigation of CEA for livestock forage production as a water-saving alternative to open-field forage production in arid regions. Forage production is a large consumer of fresh water in many arid regions of the world, including the southwestern U.S. and northern Mexico. With increasing competition among uses (agriculture, municipalities, industry, recreation, ecosystems, etc.) for limited fresh water supplies, agricultural practice alternatives that can potentially maintain or enhance productivity while reducing water use warrant consideration. The project established a pilot forage production greenhouse facility in southern New Mexico based on a relatively modest and passive (no active heating or cooling) system design pioneered in Chihuahua, Mexico. Experimental operations were initiated in August 2004 and carried over into early-FY05 to collect data and make initial assessments of operational and technical system performance, assess forage nutrition content and suitability for livestock, identify areas needing improvement, and make initial assessment of overall feasibility. The effort was supported through the joint leveraging of late-start FY04 LDRD funds and bundled CY2004 project funding from the New Mexico Small Business Technical Assistance program at Sandia. Despite lack of optimization with the project system, initial results show the dramatic water savings potential of hydroponic forage production compared with traditional irrigated open field practice. This project produced forage using only about 4.5% of the water required for equivalent open field production. Improved operation could bring water use to 2% or less. The hydroponic forage production system and process used in this project are labor intensive and not optimized for minimum water usage. Freshly harvested hydroponic forage has high moisture content that dilutes its nutritional value by requiring that livestock consume more of it to get the same nutritional content as conventional forage. In most other aspects the nutritional content compares well on a dry weight equivalent basis with other conventional forage. More work is needed to further explore and quantify the opportunities, limitations, and viability of this technique for broader use. Collection of greenhouse environmental data in this project was uniquely facilitated through the implementation and use of a self-organizing, wirelessly networked, multi-modal sensor system array with remote cell phone data link capability. Applications of wirelessly networked sensing with improved modeling/simulation and other Sandia technologies (e.g., advanced sensing and control, embedded reasoning, modeling and simulation, materials, robotics, etc.) can potentially contribute to significant improvement across a broad range of CEA applications
Recommended from our members
Development of a structural health monitoring system for the life assessment of critical transportation infrastructure.
Recent structural failures such as the I-35W Mississippi River Bridge in Minnesota have underscored the urgent need for improved methods and procedures for evaluating our aging transportation infrastructure. This research seeks to develop a basis for a Structural Health Monitoring (SHM) system to provide quantitative information related to the structural integrity of metallic structures to make appropriate management decisions and ensuring public safety. This research employs advanced structural analysis and nondestructive testing (NDT) methods for an accurate fatigue analysis. Metal railroad bridges in New Mexico will be the focus since many of these structures are over 100 years old and classified as fracture-critical. The term fracture-critical indicates that failure of a single component may result in complete collapse of the structure such as the one experienced by the I-35W Bridge. Failure may originate from sources such as loss of section due to corrosion or cracking caused by fatigue loading. Because standard inspection practice is primarily visual, these types of defects can go undetected due to oversight, lack of access to critical areas, or, in riveted members, hidden defects that are beneath fasteners or connection angles. Another issue is that it is difficult to determine the fatigue damage that a structure has experienced and the rate at which damage is accumulating due to uncertain history and load distribution in supporting members. A SHM system has several advantages that can overcome these limitations. SHM allows critical areas of the structure to be monitored more quantitatively under actual loading. The research needed to apply SHM to metallic structures was performed and a case study was carried out to show the potential of SHM-driven fatigue evaluation to assess the condition of critical transportation infrastructure and to guide inspectors to potential problem areas. This project combines the expertise in transportation infrastructure at New Mexico State University with the expertise at Sandia National Laboratories in the emerging field of SHM