Evaluation of ASR in concrete using acoustic emission and deep learning
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The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 900,000 reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 5,500 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides de-identified report information through the online ASRS Database at http://asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation \vill discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 million reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 M reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
This study demonstrates the efficacy of supplementary cementitious materials (SCMs) to mitigate alkali-silica reaction (ASR) even when used in conjunction with cement of higher alkali contents (up to 1% Na{sub 2}O{sub eq}). The expansion of concrete prisms was studied immersed in simulated pore solution in order to address the limitations of conventional ASR testing methods, accelerated mortar bar test (AMBT) and concrete prism test (CPT). Expansion results demonstrate that 25% fly ash and 50% slag are both sufficient to mitigate ASR even with cements with alkali content up to 1% Na{sub 2}O{sub eq} and that the pore solution method is a viable alternative ASR testing method. Massive amounts of ASR products (~20 μm thickness) were observed in concretes without SCMs consistent with high degree of expansion and extensive cracking. Small amounts of ASR products (≤5 μm thickness) were also observed in concrete with SCMs despite absence of significant expansion.
The Damage Rating Index (DRI), a semi-quantitative microscopic procedure, has been successfully used to describe alkali-silica reaction (ASR) damage development of concrete under “free expansion” conditions. Yet, the confinement impact on ASR-induced cracks' generation and propagation has not been fully investigated. This work aims to understand the influence of confinement on ASR development through the DRI. Eighteen concrete blocks incorporating a highly reactive coarse aggregate and distinct reinforcement configurations were manufactured, stored in conditions enabling ASR development, and monitored over time. Two expansion levels were selected for analysis (0.08% and 0.15%) and once reached, cores were extracted from three different directions (longitudinal, transverse and vertical) and the DRI conducted on those. Results demonstrate that ASR-induced expansion and deterioration change according to the direction and confinement configuration. Moreover, distinct crack features and orientations are generated in confined concrete, which attests that ASR displays different damage mechanisms under free and confinement conditions.
Alkali-silica reaction (ASR) is one of the most important concrete durability issues worldwide. ASR products formed at high temperature have a structure similar to the natural mineral shlykovite. Reactive Grand Canonical Simulations were used to investigate sorption of K{sup +}, Cl{sup −} and Ca{sup 2+} on C-S-H and ASR products at different pH (10.0 to 13.0) and pore water chemistry. Divalent ions can overcompensate for the negative surface charge, in particular for C-S-H, which leads to a co-adsorption of negative species such as Cl{sup −}. At high K/Ca in solution, monovalent K{sup +} can desorb calcium from C-S-H and shlykovite surface. The calculated Ca/K partition coefficient shows a higher affinity of ASR product for K{sup +}, while C-S-H favours Ca{sup 2+}. The uptake of K{sup +} by ASR products lowers the alkali concentration in the solution and could thus slow down the rate of ASR.
Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database. Augmenting the discovery of topics of user interest in this online database would therefore be beneficial to the community it serves. Aim: We propose and execute an experiment to assess the use of seed term topic modeling using the database narratives to identify UAS reports. The use of seed term topic modeling would enable users to identify groups of related narratives associated to a topic of their interest. Method: We use a newly curated field in ASRS reports which identify UAS from non-UAS reports in combination of different set of UAS related terms to assess if seed topic modeling can be used in ASRS.
The ASR products in concrete have various chemical compositions. It is yet unclear whether and how these products develop micro-expansion upon moisture ingress. This paper presents a 3D in-situ observation of the crystallography and volume change of an ASR-product-filled vein under varying relative-humidity (R.H.). The vein was observed to contain two layered nano-crystalline phases with distinct basal spacings, and was distributed heterogeneously in space. When R.H. changed from 10% to >38%, the basal spacing increased from 7.43 Å to 8.89 Å for one phase, whereas it remained constant (~10.9 Å) for the other. This is the first time that an ASR product is observed in-situ to exhibit crystal structural expansion during wetting process. However, the product-filled vein exhibited no noticeable swelling when R.H. varied from 10% to 97%. Our findings provide the first direct evidence that the moisturization-induced crystal structural change of ASR product may not be a plausible explanation to the macroscale concrete expansion.
Alkali-silica reaction (ASR) mitigation mechanisms of fly ash in concrete are still being debated and remain an interesting research topic. This study provides new insights into the role of aluminum oxide (Al{sub 2}O{sub 3}) in fly ash particles on ASR mitigation. A comprehensive test program was conducted and included expansion measurements, dissolution model experiments of exposed and embedded borosilicate glass elements, analyses of pore and immersion solutions, quantification of Ca(OH){sub 2} content, and microstructural analyses. It was found that in addition to the traditionally accepted mitigation mechanisms such as alkali binding, diffusion control and reduction in available Ca(OH){sub 2}, dissolution control of reactive aggregates by aluminum discharged from fly ash particles also contributed to the ASR mitigation. Re-introducing alkalis to fly ash-incorporated concrete prisms which exhibited undeleterious expansion under a long-term ASR exposure triggered and significantly increased the subsequent expansion.
The process of ASR (Alkali-Silica Reaction) induced expansion and damage in pavement concrete specimens is investigated using laboratory experiments and computational modeling. In the experimental program, the concrete specimens are subject to CS-CPT (climate simulation concrete prism test) to obtain ASR induced expansion with and without external supply of alkali. The dissolution rates of the granodiorite used in the concrete mix and the gel formation rates are determined under concrete-like conditions (pH 13.8, with/without Ca(OH){sub 2} and NaCl) at different temperatures. A micromechanics based computational model with aggregate-scale diffusion and reaction kinetics coupled to an Eigenstrain based micromechanics damage model is developed for the simulation of ASR induced expansion and damage. Data from the experimental program are used to calibrate and validate the computational model. Model predictions show that for the given concrete mixture, ASR induced expansion in the specimen exposed to water is predominantly governed by microcracking in the aggregate, while the expansion in the specimen subjected to external alkali supply is governed by microcracking in both the aggregates and the cement paste.
The alkali–silica reaction (ASR) is a phenomenon that leads to material degradation in concrete, resulting in the formation of microcracks and cracks. This deterioration causes a loss of mechanical properties, concrete damage, and even corrosion. To address this issue, ultrasonic nondestructive evaluation can be employed as a technique for long-term monitoring of ASR development and condition assessment of concrete subjected to ASR. However, traditional approaches typically utilize only a few wave parameters, such as wave velocity or amplitude, to characterize ASR-induced concrete damage while disregarding the majority of information present in the ultrasonic signals.
To support Search Requests and Quick Responses at the Aviation Safety Reporting System (ASRS), four new QUORUM methods have been developed: keyword search, phrase search, phrase generation, and phrase discovery. These methods build upon the core QUORUM methods of text analysis, modeling, and relevance-ranking. QUORUM keyword search retrieves ASRS incident narratives that contain one or more user-specified keywords in typical or selected contexts, and ranks the narratives on their relevance to the keywords in context. QUORUM phrase search retrieves narratives that contain one or more user-specified phrases, and ranks the narratives on their relevance to the phrases. QUORUM phrase generation produces a list of phrases from the ASRS database that contain a user-specified word or phrase. QUORUM phrase discovery finds phrases that are related to topics of interest. Phrase generation and phrase discovery are particularly useful for finding query phrases for input to QUORUM phrase search. The presentation of the new QUORUM methods includes: a brief review of the underlying core QUORUM methods; an overview of the new methods; numerous, concrete examples of ASRS database searches using the new methods; discussion of related methods; and, in the appendices, detailed descriptions of the new methods.
ASRS is conducting a structured callback research project of wake vortex incidents reported to the ASRS at all US airports, as well as wake encounters in the enroute environment. This study has three objectives: (1) Utilize the established ASRS supplemental data collection methodology and provide ongoing analysis of wake vortex encounter reports; (2) Document event dynamics and contributing factors underlying wake vortex encounter events; and (3) Support ongoing FAA efforts to address pre-emptive wake vortex risk reduction by utilizing ASRS reporting contributions.
NASA’s Aviation Safety Reporting System (ASRS) database is the world's largest repository of voluntary, confidential safety information provided by aviation's frontline personnel, including pilots, air traffic controllers, mechanics, flight attendants, dispatchers, and other members of the aviation community and the public. The database contains close to 2 million narratives, many of which describe everyday situations in which people saved the day. In these situations, people’s resilient behavior solved a problem, dealt with a malfunction, and maintained a safe operation despite a serious perturbation. To be able to extract lessons of such resilience from this large database, the use of machine learning algorithms is being explored. In this report, we describe a comparison between two such algorithms: Perilog and Word2Vec. An identical search using both programs was done on a database containing approximately 470,000 ASRS reports submitted between 1988 and 2022. The comparison reveals some of the strength and weaknesses of each algorithm as well as the challenges inherent in using such algorithms to extract lessons of resilience from the ASRS database.
Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.
This paper discusses the use of computer-assisted instructions and flight simulations to enhance procedural and perceptual motor task training. Attention is called to the fact that incorporating the accident and incident data contained in reports filed with the Aviation Safety Reporting System (ASRS) would be a valuable training tool which the learner could apply for other situations. The need to segment the events is emphasized; this would make it possible to modify events in order to suit the needs of the training environment. Methods were developed for designing meaningful scenario development on runway incursions on the basis of analysis of ASRS reports. It is noted that, while the development of interactive training tools using the ASRS and other data bases holds much promise, the design and production of interactive video programs and laser disks are very expensive. It is suggested that this problem may be overcome by sharing the costs of production to develop a library of materials available to a broad range of users.
Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential system that disseminates reports received from personnel involved in aviation operations after de-identifying them. These reports are used by the community to improve overall aviation system safety. Aim: We propose and execute an experiment to assess the use of seed term topic modeling over the database narratives to identify Unmanned Aircraft System (UAS) reports. The use of seed term topic modeling enables users to identify groups of conceptually similar narratives associated to a topic of their interest. Method: We use a collection of narratives, expert-selected words, and report metadata that separates UAS from non-UAS reports to assess if seed topic modeling can be used to improve ASRS searches. Results: For simpler queries, seed topic search observes a higher recall and lower precision than the existing DBOL (DataBase OnLine) search in operation. However, the best results are obtained when seed topic search is used as a search suggestion system to be executed on the DBOL. Conclusion: Utilizing a combination of both the existing method and the proposed method, users can expand their search vocabulary about subjects of interest while improving the quality of results.